Relevant bibliographies by topics / Cancer chemotherapy; Intelligent search

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Cancer chemotherapy; Intelligent search'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Cancer chemotherapy; Intelligent search"

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Moore, Halle C. F., Michael W. Parsons, Guang H. Yue, Lisa A. Rybicki, and Vlodek Siemionow. "EEG for evaluation of “chemobrain.”." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 1076. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.1076.

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1076 Background: Cognitive impairment is a poorly understood and worrisome potential complication of adjuvant chemotherapy (CT). We sought to evaluate electroencephalography (EEG) as a means to measure neurophysiologic function in women receiving CT for early breast cancer. Methods: Women planning to undergo CT for operable breast cancer and age-similar controls were evaluated at baseline, during CT and at 1 year with neurophysiologic assessments. Testing included a brief fatigue inventory (BFI), brief mental fatigue assessment (BMF), Processing Speed Index (PSI) derived from Digit Symbol Coding and Symbol Search subtests of the Wechsler Adult Intelligence Scale, and a sustained elbow flexion physical task (PT). EEG recordings were obtained at rest and after the cognitive and physical tasks. Data were analyzed using repeated measures of analysis of variance. Results: Eight patient/control pairs completed baseline and on-treatment evaluations; 7 pairs also completed the 1 year assessment (1 pair withdrawn due to a second malignancy). Subjective mental fatigue measured by BMF is similar for patients and controls at baseline but BMF scores increase significantly during CT for patients relative to controls (p=0.033), recovering to no difference at one year. Differences in PSI are not observed between patients and controls or at the different time points. BFI scores are greater in patients at all 3 time points but endurance on the PT is no different from controls. During chemotherapy EEG total spectrum amplitudes in patients are greater than in controls at rest (p=0.05) and following both the cognitive (p<0.001) and physical (p<0.001) tasks. EEG activity prior to chemotherapy and at one year is not different between patients and controls. For patients but not controls EEG readings after the cognitive task demonstrate greater amplitude than pre-task readings during the time of CT treatment only (p=0.012) with a similar trend seen for the physical task (p=0.06). Conclusions: Patient-perceived mental and physical fatigue during chemotherapy correspond to significant changes in EEG brain activity patterns but not to cognitive testing or physical endurance testing. EEG may offer a sensitive means to measure alterations in brain function associated with CT.
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Su, Ashley, Léonie Dupuis, Jeremy Jueng, Anuj Kunadia, Ian Brooks, Ritika Sinha, Fahad Siddiqui, et al. "Use of artificial intelligence for analyzing emotion vs patient global impression of change of melanoma treatments." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e24177-e24177. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e24177.

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e24177 Background: The link between melanoma patients’ emotions and their impressions of treatments response are poorly understood. With the rise of social media, patients use online platforms to communicate their concerns related to melanoma treatments. In this study, we utilize real-world data collected from social media with search terms focused on treatment-specific Patients’ Global Impression of Change (PGIC) compared with their emotions. We aim to identify and focus melanoma patient perspective trends to improve patient-centered care. Methods: Social media data mining of search terms were extracted from millions of publicly available interactions on Twitter and other online platforms from May/2008 to January/2020 using Crimson Hexagon (database of real-time social media posts). Results: For chemotherapy posts, the top three emotions by volume were negative alongside negative PGIC “worse” (Worse/Sadness 700, Worse/Fear 596, Worse/Disgust 403, and “decline” (Decline/Sadness 262, Decline/Fear 186, Decline/Disgust 57). Interestingly, Sadness, Fear, and Disgust were as prevalent alongside positive PGIC “well” and “cured” (Well/Sadness 3577, Well/Fear 2545, and Well/Disgust 1770; Cured/Sadness 518, Cured/Disgust 275, and Cured/Fear 167). For Keytruda treatment posts, emotions in negative PGIC “worse” were (Worse/Fear 117, Worse/Anger 68, Worse/Sadness 6). In positive PGIC “well”, results were (Well/Fear 880, Well/Sadness 366, Well/Anger 186). Further analysis will compare these emotional sentiments with a spectrum of PGIC terms and specific types of melanoma treatments. Conclusions: To our knowledge, this is the first investigation of online patient melanoma treatments associated with PGIC terms. The findings indicate a trend of negative emotions even when patients have reported wellness or being cured by treatment. While treatments may be effective, patients are not necessarily satisfied. Correlating changes in emotions with perceived changes in disease severity can provide insight into patient perspectives, which has implications in translating clinical response and a need for continued emotional support in patients with treatment response.
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Murad Junior, Munir, Arthur Nascimento, Alexandre Fonseca De Castro, Lilian Paiva, Amandio S. Fernandes, and Luiz Adelmo Lodi. "The use of a chatbot based on artificial intelligence to collect patients reported outcomes in oncology practice. A pilot study with real-world data." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19119-e19119. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19119.

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e19119 Background: There is growing interest in enhancing symptoms monitoring during routine cancer care using patient-reported outcomes (PROs). The quality of evidence that demonstrates clinical benefits of this type of assistance is also increasing. However, the best method for this approach is evolving and there are many barriers to implement these tools in the real world scenario. We aim to describe a pilot study about a chatbot with artificial intelligence developed to collect PROs and to optimize adherence to systemic cancer treatment. Methods: This is a case series that reports the first patients in a private oncology clinic in Belo Horizonte, Southeast Brazil who consecutively underwent regular conversations with a chatbot based on artificial intelligence. Data was collected from February the 23th to December the 3rd 2019. The virtual assistant interacted with the patient in four different ways, being the first three of these an active search from the chatbot: a) search for adverse events, b) adherence to oral treatment c) screening for depression d) spontaneous patient demand (not an active search). Results: Interaction with the chatbot was offered to 193 patients. A total of 107 patients were included. Of these 74% were female, 55% older than 60 years and 22% had at least 7 years education.194 protocols of treatment were analysed, 66% of these being chemotherapy regimens and 23% hormone therapy. Oral drugs corresponded to 23% of the protocols. The main adverse events reported were fatigue 20%, nausea 13%, pain 11%, diarrhea 10%, lack of appetite 6%. Adverse effects were classified by patients as grade III or IV approximately 24% of the time. For patient safety the system runs a script twice a day to detect any adverse effect and send it to the service attended. A total of 3883 dialogues were initiated, the majority of which (3772) was carried out by the machine. Only 3% of the dialogues were spontaneously initiated by the patients. Once the conversation started, adherence was considerably satisfactory since engagement was 73% for questions about adherence to oral medications and 76% of people reported at least one adverse event. Conclusions: An initial barrier must be surpassed since the chatbot was offered to 193 patients and 86 (44%) did not register for use. Once the contact started, we understand that the use of AI is promising since the engagement rates were very good. It is important to highlight the potential capacity for early identification of symptoms since most dialogues were initiated by the virtual assistant.
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Souza, Juliana, and Daniele Neves. "Active search for toxicity reduces delay on chemotherapy." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): 6548. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.6548.

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6548 Background: Interdisciplinary teamwork involves health care professionals working as a team with the purpose of discussing individual cases and recommending care plans. In october 2015, the breast cancer interdisciplinary team (BCIT) was implemented in our outpatient oncology clinic. This team includes oncology physician, pharmaceutist, psychologist, nutritionist and oncology nurse. Since 2018, the oncology nurse does active search for toxicity (AST) in order to solve early symptoms. Methods: We evaluated outcomes of breast cancer patients who finished neoadjuvant/adjuvant chemotherapy and received BCIT care at our oncology clinic from october 2015 to November 2018. Results: Of 200 pts who had finish treatment, 139 pts (69.5%) received adjuvant chemotherapy and 61 pts (30.5%) neoadjuvant schedule. Median age was 52,64 years (range:30.6-82.3y). At diagnosis, 50 pts (25%) were stage I, 101 pts (50.5%) were stage II, and 49 pts (24.5%) were stage III. When we compared before and after AST, there were no significant difference between mean age (54.13y vs 54.06y, p:0.97), colony stimulating factor use (p:0.10), cold-cap use (p:0.81), and timing of chemotherapy (p:0.13). There were 7 hospitalizations during chemotherapy, with no significant difference with AST (5pt vs 2pt, p: 0.82). However, patients in AST had significantly lower mean delay to complete chemotherapy (9.4 days vs 4.2 days p:0.003). After median follow up 17 months, there were 9 progression disease and 4 deaths. 1-year and 3-year overall survival rate was 99,2% and 95,1%, respectively. Conclusions: AST increased adherence to chemotherapy, with lower delay on chemotherapy treatment. There were no significant difference with colony stimulating factor use, cold-cap use, timing of chemotherapy, and hospitalization.
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Harrington, K. J., and H. E. Lambert. "The search for optimal chemotherapy for advanced epithelial ovarian cancer." Clinical Oncology 7, no. 6 (January 1995): 359–65. http://dx.doi.org/10.1016/s0936-6555(05)80005-6.

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Berenbaum, MC. "Direct search methods in the optimisation of cancer chemotherapy regimens." British Journal of Cancer 61, no. 1 (January 1, 1990): 101–9. http://dx.doi.org/10.1038/bjc.1990.22.

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Luo, Shiyao, Ying Zhu, Yiping Li, Li Chen, Shunzhong Lv, Yuan Zhang, Liang Ge, and Wenwu Zhou. "Targeted Chemotherapy for Breast Cancer Using an Intelligent Doxorubicin-Loaded Hexapeptide Hydrogel." Journal of Biomedical Nanotechnology 16, no. 6 (June 1, 2020): 842–52. http://dx.doi.org/10.1166/jbn.2020.2935.

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Self-assembling peptide hydrogels have a high water content, good biocompatibility and have become a competitive research object in the fields of tissue engineering, cancer treatment and drug delivery. In our research, a hexapeptide with high pH sensitivity was designed and synthesized by utilizing a solid-phase synthesis method. Under physiological conditions, the peptide could self-assemble into a hydrogel. When it reached the tumor acidic microenvironment, the peptide was degraded and doxorubicin was released to exert its antitumor effect. A series of physicochemical properties were investigated, including gelling ability, secondary structure, micromorphology, rheological properties and drug release studies. The results illustrated that PIDO peptide hydrogel has good pH responsiveness and injectability. In vitro cytotoxicity experiments and in vivo antitumor experiments showed that PIDO peptide hydrogel has a highly effective therapeutic effect on tumor cells and is less toxic to normal tissues. Our research provides a promising option for targeted drug delivery and sustainable release.
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Jing, Xunan, Yanzi Xu, Daomeng Liu, Youshen Wu, Na Zhou, Daquan Wang, Kai Yan, and Lingjie Meng. "Intelligent nanoflowers: a full tumor microenvironment-responsive multimodal cancer theranostic nanoplatform." Nanoscale 11, no. 33 (2019): 15508–18. http://dx.doi.org/10.1039/c9nr04768a.

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Multistage pH/H2O2/redox-responsive 3D nanoflowers that fully exploit the tumor microenvironment achieve highly specific guided multimode diagnosis with excellent synergistic chemotherapy and photodynamic therapy effects both in vitro and in vivo.
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Kilgallen, Aoife B., Urška Štibler, Markella I. Printezi, Marrit Putker, Cornelis J. A. Punt, Joost P. G. Sluijter, Anne M. May, and Linda W. van Laake. "Comparing Conventional Chemotherapy to Chronomodulated Chemotherapy for Cancer Treatment: Protocol for a Systematic Review." JMIR Research Protocols 9, no. 10 (October 21, 2020): e18023. http://dx.doi.org/10.2196/18023.

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Background Chronomodulated chemotherapy aims to achieve maximum drug safety and efficacy by adjusting the time of treatment to an optimal biological time as determined by the circadian clock. Although it is a promising alternative to conventional (non–time-stipulated) chemotherapy in several instances, the lack of scientific consensus and the increased logistical burden of timed administration limit the use of a chronomodulated administration protocol. Objective With the goal to increase scientific consensus on this subject, we plan to conduct a systematic review of the current literature to compare the drug safety and efficacy of chronomodulated chemotherapy with those of conventional chemotherapy. Methods This systematic review will comply with the PRISMA (Preferred Reporting Items for the Systematic Reviews and Meta-Analysis) guidelines. In order to identify relevant studies, we conducted a comprehensive search in PubMed and Embase on May 18, 2020. We included clinical studies that compare either the safety or efficacy of chronomodulated chemotherapy with that of conventional chemotherapy. Potential studies will be reviewed and screened by 2 independent reviewers. Quality assessment will be performed using the National Institutes of Health’s Study Quality Assessment Tool (Quality Assessment of Controlled Intervention Studies). Disagreements will be resolved by consulting a third independent reviewer. Results This protocol has received funding, and the search for studies from databases commenced on May 18, 2020. The systematic review is planned to be completed by October 31, 2020. Conclusions In this systematic review, we will compare drug safety and drug efficacy for cancer patients who were administered either chronomodulated chemotherapy or conventional chemotherapy. Moreover, we will highlight the outcomes and quality of the selected trials for this review. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42020177878; https://tinyurl.com/y53w9nq6 International Registered Report Identifier (IRRID) PRR1-10.2196/18023
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Hu, Cheng, Weihua Zhuang, Tao Yu, Liang Chen, Zhen Liang, Gaocan Li, and Yunbing Wang. "Multi-stimuli responsive polymeric prodrug micelles for combined chemotherapy and photodynamic therapy." Journal of Materials Chemistry B 8, no. 24 (2020): 5267–79. http://dx.doi.org/10.1039/d0tb00539h.

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Dissertations / Theses on the topic "Cancer chemotherapy; Intelligent search"

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Petrovski, Andrei. "An application of genetic algorithms to chemotherapy treatment." Thesis, Robert Gordon University, 1998. http://hdl.handle.net/10059/1259.

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The present work investigates methods for optimising cancer chemotherapy within the bounds of clinical acceptability and making this optimisation easily accessible to oncologists. Clinical oncologists wish to be able to improve existing treatment regimens in a systematic, effective and reliable way. In order to satisfy these requirements a novel approach to chemotherapy optimisation has been developed, which utilises Genetic Algorithms in an intelligent search process for good chemotherapy treatments. The following chapters consequently address various issues related to this approach. Chapter 1 gives some biomedical background to the problem of cancer and its treatment. The complexity of the cancer phenomenon, as well as the multi-variable and multi-constrained nature of chemotherapy treatment, strongly support the use of mathematical modelling for predicting and controlling the development of cancer. Some existing mathematical models, which describe the proliferation process of cancerous cells and the effect of anti-cancer drugs on this process, are presented in Chapter 2. Having mentioned the control of cancer development, the relevance of optimisation and optimal control theory becomes evident for achieving the optimal treatment outcome subject to the constraints of cancer chemotherapy. A survey of traditional optimisation methods applicable to the problem under investigation is given in Chapter 3 with the conclusion that the constraints imposed on cancer chemotherapy and general non-linearity of the optimisation functionals associated with the objectives of cancer treatment often make these methods of optimisation ineffective. Contrariwise, Genetic Algorithms (GAs), featuring the methods of evolutionary search and optimisation, have recently demonstrated in many practical situations an ability to quickly discover useful solutions to highly-constrained, irregular and discontinuous problems that have been difficult to solve by traditional optimisation methods. Chapter 4 presents the essence of Genetic Algorithms, as well as their salient features and properties, and prepares the ground for the utilisation of Genetic Algorithms for optimising cancer chemotherapy treatment. The particulars of chemotherapy optimisation using Genetic Algorithms are given in Chapter 5 and Chapter 6, which present the original work of this thesis. In Chapter 5 the optimisation problem of single-drug chemotherapy is formulated as a search task and solved by several numerical methods. The results obtained from different optimisation methods are used to assess the quality of the GA solution and the effectiveness of Genetic Algorithms as a whole. Also, in Chapter 5 a new approach to tuning GA factors is developed, whereby the optimisation performance of Genetic Algorithms can be significantly improved. This approach is based on statistical inference about the significance of GA factors and on regression analysis of the GA performance. Being less computationally intensive compared to the existing methods of GA factor adjusting, the newly developed approach often gives better tuning results. Chapter 6 deals with the optimisation of multi-drug chemotherapy, which is a more practical and challenging problem. Its practicality can be explained by oncologists' preferences to administer anti-cancer drugs in various combinations in order to better cope with the occurrence of drug resistant cells. However, the imposition of strict toxicity constraints on combining various anticancer drugs together, makes the optimisation problem of multi-drug chemotherapy very difficult to solve, especially when complex treatment objectives are considered. Nevertheless, the experimental results of Chapter 6 demonstrate that this problem is tractable to Genetic Algorithms, which are capable of finding good chemotherapeutic regimens in different treatment situations. On the basis of these results a decision has been made to encapsulate Genetic Algorithms into an independent optimisation module and to embed this module into a more general and user-oriented environment - the Oncology Workbench. The particulars of this encapsulation and embedding are also given in Chapter 6. Finally, Chapter 7 concludes the present work by summarising the contributions made to the knowledge of the subject treated and by outlining the directions for further investigations. The main contributions are: (1) a novel application of the Genetic Algorithm technique in the field of cancer chemotherapy optimisation, (2) the development of a statistical method for tuning the values of GA factors, and (3) the development of a robust and versatile optimisation utility for a clinically usable decision support system. The latter contribution of this thesis creates an opportunity to widen the application domain of Genetic Algorithms within the field of drug treatments and to allow more clinicians to benefit from utilising the GA optimisation.
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Börjeson, Sussanne. "Nausea and emesis in cancer chemotherapy : aspects of occurrence, assessment and treatment /." Stockholm, 1998. http://diss.kib.ki.se/search/diss.se.cfm?19980512borj.

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McLaren, Susan R. A. "The generation of recombinant phage antibodies to the multiple drug resistance protein P-glycoprotein." Thesis, University of Aberdeen, 1997. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU104246.

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The generation of human antibodies to the multiple drug resistance protein, P-glycoprotein (Pgp), has been a challenge in the field of cancer chemotherapy since drug resistance was first described. Pgp was identified as being an intrinsic factor in the resistance to chemotherapeutic drugs, as its levels were found to escalate after primary drug challenges. Further investigation into the structure and function of P-glycoprotein elucidated that its activity was ATP dependent, and that it had broad spectrum specificity. In order to augment the success of chemotherapeutic treatment of patients it was deemed necessary to regulate the activity of this protein. This was possible by physical inhibition of its activity or through regulation at the genetic level. This project addresses the former of the two options, the physical inhibition of Pgp activity. It was considered that by the generation of antibodies to the extracellular regions of Pgp it would be possible to inhibit its activities. For such antibodies to be effective in the human model, the antibodies would have to bear human determinants in order that the human immune system would not attach and destroy these antibodies before they had the desired effect. Therefore it was decided that recombinant phage technology should be used. This is a system which selects single chain antibodies with human determinants from a large and diverse population of antibodies with a variety of specificities. Initially, attempts were made to generate a phage library de novo using a commercial kit designed for this purpose. However, after repeated attempts at this process, this approach was found to be beyond technical abilities, and was rejected in favour of a more rudimentary approach. Two libraries were screened for antibodies which would bind to membrane preparations from two leukaemic cell lines, CCRF CEM and CCRF CEM VLB. The former cell line was a drug-sensitive cell line which responded favourably to drug challenge, and the latter was a drug-resistant cell line which thrived in drug-rich environments. The drug-resistant cell line was derived from the drug-sensitive cell line, and was considered to be identical in all respects except drug sensitivity. Antibodies obtained from a large multicombinatorial library, the Lox library, were found to display selective binding to CCRF CEM VLB cell membranes in favour of CCRF CEM cell membranes. Antibodies were also generated to peptides representing the 6 extracellular loops of Pgp. From these selections antibodies were generated which were found to selectively bind the peptide to which they had been raised.
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Laatio, L. (Liisa). "In search of new prognostic molecular markers in ovarian cancer." Doctoral thesis, Oulun yliopisto, 2012. http://urn.fi/urn:isbn:9789514298349.

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Abstract Ovarian cancer is the leading cause of death from gynaecological cancers in the Western world. Ovarian cancer comprises of tumours with distinct behaviour and individually different responses to chemotherapy, even within the same histology. Unfortunately, there are no molecular markers in clinical use to either distinguish between patients with better and worse prognosis or to predict individual chemosensitivity. The comprehension of the molecular effects of chemotherapeutic drugs is a prerequisite for finding predictive molecular factors for chemoresponse and prognosis. Some proteins in molecular pathways contributing to DNA damage response, angiogenesis and oxidative stress have been implicated in ovarian cancer prognosis. In this study, the responses in p53 pathway and among angiogenesis-related factors to chemotherapeutic drugs were analysed in ovarian cancer cell lines. In OVCAR-3 cells with mutated p53, cisplatin but not docetaxel induced p14ARF, an important regulator of p53, at mRNA and protein level. Cisplatin also significantly increased the mRNA expression of angiogenesis-related factors TSP-1, BMP-4, ET-1 and PlGF-2 while an equivalent dose of docetaxel had only minor effects. In clinical ovarian carcinomas, the expression of BMP-4, TSP-1 and CD105 as well as the marker of oxidative stress derived DNA damage, 8-OHdG, and peroxiredoxin antioxidants were analysed by immunohistochemistry. High expression of BMP-4 and cytoplasmic peroxiredoxin IV were associated with better prognosis, while high 8-OHdG expression associated with shorter survival. Explant cultures of fresh ovarian tumour tissue were used for the evaluation of individual responses of p53 and Hdm2 after in vitro treatments of the explant cultures by carboplatin or docetaxel. Major differences between the individual tumours were found, especially in the responses of p53 to carboplatin. The results of this study suggest, that BMP-4, 8-OHdG and peroxiredoxin IV may serve as prognostic markers in ovarian cancer. The differences shown in the molecular responses to platinum and taxane drugs may have value in tailoring individual chemotherapy. Also, fresh ovarian cancer tissue explant culture is worth further studies as a predictive method for analysing individual tumour responses for chemotherapeutic agents
Tiivistelmä Munasarjasyöpä on suurinta kuolleisuutta aiheuttava gynekologinen syöpä läntisessä maailmassa. Munasarjakasvaimet eroavat toisistaan niin käyttäytymiseltään kuin yksilölliseltä sytostaattihoitovasteeltaan, jopa sama histologisen tyypin sisällä. Kliinisessä käytössä ei valitettavasti ole sellaisia molekulaarisia merkkiaineita, jotka erottaisivat toisistaan paremman ja huonomman ennusteen kasvaimet tai ennustaisivat yksilöllistä solunsalpaajaherkkyyttä. Hoitovastetta ja potilaan prognoosia ennustavien merkkiaineiden löytämisen edellytys on kemoterapian molekyylitason vaikutusten ymmärtäminen. DNA vaurion tunnistamiseen, angiogeneesiin ja oksidatiiviseen stressiin liittyvien vaikutusreittien joillakin proteiineilla on ehdotettu olevan ennusteellista merkitystä munasarjasyövässä. Tässä väitöskirjatyössä analysoitiin munasarjasyöpäsoluja käyttäen p53 vaikutusreitin ja eräiden angiogeneesiin liittyvien tekijöiden vasteita sytostaateille. Mutatoitunutta p53 proteiinia kantavissa OVCAR-3 soluissa sisplatiini, toisin kuin dosetakseli, indusoi p53 proteiinin tärkeää säätelijää, p14ARF:a sekä mRNA- että proteiinitasolla. Sisplatiini lisäsi merkittävästi myös usean angiogeneesiin liittyvän tekijän (TSP-1, BMP-4, ET-1 ja PlGF-2) mRNA:ta. Dosetakselin vaikutukset vastaavalla annoksella olivat vähäiset. Kliinisissä munasarjasyövissä BMP-4, TSP-1 ja CD105 sekä oksidatiivisen stressin aiheuttaman DNA-vaurion merkkiaineen, 8-OHdG:n sekä peroksiredoksiiniantioksidanttien ilmeneminen analysoitiin immunohistokemiallisesti. BMP-4:n ja sytoplasmisen peroksiredoksiini IV:n vahva ilmentyminen liittyivät parempaan ennusteeseen, kun taas 8-OHdG:n vahva ilmentyminen liittyi huonompaan elinajan ennusteeseen. Tuoreen munasarjasyöpäkudoksen eksplanttiviljelyn avulla selvitettiin p53 ja Hdm2 proteiinien vasteita syöpäkudoksen karboplatiini- tai dosetakseli-käsittelyille. Selkeitä yksilökohtaisia eroja havaittiin erityisesti karboplatiinin aiheuttamissa p53 vasteissa niin eri potilaiden kuin eri histologisten kasvaintyyppien välillä. Tämän väitöskirjatutkimuksen tulokset antavat viitteitä BMP-4:n, 8-OHdG:n ja peroksiredoksiinin mahdollisesta ennusteellisesta merkityksestä munasarjasyövässä. Erot platinayhdisteiden ja taksaanien välillä saattavat osoittautua merkittäviksi yksilöllisiä syövän hoitoja räätälöitäessä. Tuoreen munasarjasyöpäkudoksen eksplanttiviljelyn mahdollisuuksia yksilöllisten kasvainten hoitovasteiden ennustamisessa kannattaa selvittää jatkotutkimuksin
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Rooney, Patrick Hugh. "A genomic approach to the study of chemoresistance." Thesis, University of Aberdeen, 2000. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU602009.

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This study evaluated comparative genomic hybridisation (CGH) as a tool to detect candidate regions of the genome associated with chemoresistance. Using a variation on conventional CGH, DNA from three cell lines that were resistant to thymidylate synthase (TS) inhibitors (tomudex [TDX] or 5-fluorouracil [5-FU]) and their sensitive parent cells were evaluated. In MCF-7 and H630, cells that were resistant to TDX, a specific TS inhibitor with no other known cytotoxic potential, only a single region of change (18p gain) was apparent. The third cell line H630R10, which was resistant to 5-FU, had changes in several genomic regions following the acquisition of resistance, including 18p. Gain in the chromosomal region containing the TS gene (18pll.32) was detected by CGH in all three resistant cell lines. However, additional novel regions of interest were identified in the cells that were resistant to 5-FU, a cytotoxic agent known to have several other modes of cytotoxicity besides TS inhibition. These results suggested that CGH is of potential use in the detection of regions of the genome involved in chemoresistance. Having shown the potential of CGH as a tool for assessing chemoresistance at the genomic level, steps toward clinical application of this technique were evaluated. A prerequisite for study in archival pathology samples was successful DNA extraction and universal amplification of tumour DNA from paraffin-embedded tumour sections for CGH analysis. Degenerate oligonucleotide primed - polymerase chain reaction (DOP-PCR) was performed on minute quantities (50ngs) of fresh cell line DNA (H630R10) and tumour DNA (osteosarcoma), as well as paraffin-embedded DNA from the same case. The results of these DOP-PCR CGH reactions were compared with conventional CGH using l|0.g quantities of fresh DNA from both H630R10 cell line and osteosarcoma. The CGH profiles of the conventional CGH and DOP-PCR CGH did not show a high level of concordance, only 55% of the gains and 83.3% of losses detected by conventional CGH were detected by DOP-PCR CGH The use of universal amplification by DOP-PCR in paraffin-embedded sections was not taken forward into clinical evaluation. A study of colorectal cancer (CRC) was initiated which involved the microdissection of 29 Dukes' C CRC tumours from fresh frozen material for CGH analysis. This conventional CGH analysis of CRC tumours involved assessing each tumour twice by reversal of fluorochromes. Only genomic regions that were detected as changed in both forward and reverse profiles were accepted. This approach detected several regions of genome as changed across the 29 tumours. In all, 108 gains (a mean number of 3.7 aberrations per tumour, range 1-12) and 85 losses (a mean number of 2.9 aberrations per tumour, range 0-11) were detected in the 29 tumours. CGH analyses identified certain chromosomal regions as more likely to be changed than others. The most frequent aberrations detected across the 29 tumours was a loss of chromosomal arm 18q, seen in 31% of the tumours assessed. Gain was also common at some sites throughout the genome, for example, gain of chromosomal arms, 13q and 20q was seen in 27.6% of cases. Mann-Whitney U tests investigating the association between specific chromosomal aberrations such as gain of 20q or loss of 18q and known markers of CRC tumourigenesis (p53, p27, p21, Rb, cyclin Dl, PCNA, P-catenin, e-cadherin, c-erbB-2, bcl2, EGFR and c-erbB-2) assessed by immunohistochemistry (IHC) in 29 tumours found no association. Testing of the total number of genomic aberrations detected (loss + gain = genetic grade) rather than the frequency of aberration at specific chromosomal loci also found no association with the CRC tumour markers. Finally, the association between the chromosomal aberrations detected by CGH was investigated in relation to patient survival. This thesis has demonstrated the value of a global approach to the study of chemoresistance and tumourigenesis through the application of powerful technology such as CGH.
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Books on the topic "Cancer chemotherapy; Intelligent search"

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(Editor), M. J. Waring, and B. A. Ponder (Editor), eds. The Search for New Anti-Cancer Drugs (Cancer Biology and Medicine). Springer, 1992.

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J, Waring Michael, and Ponder, B. A. J. 1944-, eds. The Search for new anticancer drugs. Dordrecht: Kluwer Academic Publishers, 1992.

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Wingard, John R. Introduction. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199938568.003.0300.

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This chapter starts by explaining that the goal of allogeneic stem cell transplantation is the establishment of donor hematopoiesis and immunity in the recipient to treat an antecedent marrow failure disorder or to achieve a graft-versus-cancer effect to treat a neoplastic disease. The goal of autologous hematopoietic stem cell transplant (HSCT) is very different from allogeneic HSCT. In autologous HSCT, the goal of the graft is simpler: it is to rescue the myelotoxic effects of high-dose chemotherapy. Neutropenia is shorter, cellular immunodeficiency is less profound, and immune reconstitution is quicker. Infectious exposures before transplant play an important role after transplant. Although an infection may be effectively treated and under good control before transplant, reactivation may occur after transplant. The search for risk factors that can identify individuals at greatest risk for various types of infection has led to the identification of neutropenia, lymphopenia (or low CD4+ cell counts), low levels of immunoglobulin, and GVHD, prior infection by organisms that may persist in the recipient or donor, and a number of other factors in certain situations. The chapter concludes that one of the biggest challenges is distinguishing infection from some other noninfectious etiology of a syndrome.
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Book chapters on the topic "Cancer chemotherapy; Intelligent search"

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Algoul, S., M. S. Alam, K. Sakib, M. A. Hossain, and M. A. A. Majumder. "MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy." In Advances in Intelligent and Soft Computing, 133–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19914-1_19.

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Panjwani, Bharti, Vijander Singh, Asha Rani, and Vijay Mohan. "Optimizing Drug Schedule for Cell-Cycle Specific Cancer Chemotherapy." In Advances in Intelligent Systems and Computing, 71–81. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1696-9_7.

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Vivek, Pandey, Pachauri Nikhil, Rani Asha, and Singh Vijander. "Optimal ISA-PID-Based Drug Concentration Control in Cancer Chemotherapy." In Advances in Intelligent Systems and Computing, 165–71. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5903-2_19.

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Stern, E. W. "The Search for New Platinum Antitumor Agents: Progress, Problems and Prospects." In Platinum and Other Metal Coordination Compounds in Cancer Chemotherapy, 519–26. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1717-3_60.

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Gyftodimos, Elias, Laura Moss, Derek Sleeman, and Andrew Welch. "Analysing PET scans data for predicting response to chemotherapy in breast cancer patients." In Applications and Innovations in Intelligent Systems XV, 59–72. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-086-5_5.

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Buttan, Yagya, Alka Chaudhary, and Komal Saxena. "An Improved Model for Breast Cancer Classification Using Random Forest with Grid Search Method." In Algorithms for Intelligent Systems, 407–15. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-6707-0_39.

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Yodpijit, Nantakrit, Manutchanok Jongprasithporn, Benjama Treeviriyakijja, Phalinnart Lai-Ngam, Siritip Boonyarit, and Teppakorn Sittiwanchai. "Human Factors Product Design for a Prototype of Hair Loss Prevention Machine for Cancer Patients During Chemotherapy Treatments." In Advances in Intelligent Systems and Computing, 882–87. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19135-1_86.

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Cyran, Krzysztof A., and Marek Kimmel. "Comparison of Connectionist and Rough Set Based Knowledge Discovery Methods in Search for Selection in Genes Implicated in Human Familial Cancer." In Advances in Intelligent Systems and Computing, 163–71. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02309-0_17.

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Rischin, Danny. "Biomarkers for Immune Modulatory Treatment in Head and Neck Squamous Cell Carcinoma (HNSCC)." In Critical Issues in Head and Neck Oncology, 83–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63234-2_6.

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AbstractImmune checkpoint inhibitors have changed the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC). However, only a minority of patients respond, hence the search for predictive biomarkers. Potential predictive biomarkers for immune checkpoint inhibitors discussed in this chapter include (1) Immune checkpoint ligand expression e.g., PD-L1, (2) biomarkers of a T-cell inflamed tumour microenvironment (TME) such as gene expression profiles of activated T cells, (3) biomarkers of tumour neoepitope burden such as tumour mutation burden (TMB) and (4) multidimensional quantitative techniques. At present only PD-L1 expression has been shown to have clinical utility in head and neck cancer. It enriches for populations more likely to respond, but the false positive predictive value remains high. In the pivotal Keynote−048 trial that established a role for pembrolizumab (anti-PD1) monotherapy and pembrolizumab + chemotherapy as treatment options in first-line R/M HNSCC, primary endpoints included overall survival in defined subgroups based on PD-L1 expression. In this trial the combined positive score (CPS) was used which takes into account PD-L1 expression in tumour and immune cells. Based on this trial regulatory approvals for first-line pembrolizumab in R/M HNSCC require assessment of PD-L1 expression using the CPS. Finally we discuss emerging evidence that locoregionally advanced HPV-associated oropharyngeal cancers that have high expression of CD103 positive CD8 T cells have an excellent prognosis and features that suggest increased probability of responding to anti-PD1/PD-L1, raising the possibility of incorporating these immune therapies as part of a de-escalation trial strategy.
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Bielack, Stefan, Michael Paulussen, and Lee Helman. "Bone Tumours." In Oxford Textbook of Cancer in Children, 219–30. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198797210.003.0026.

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This chapter reviews the biology, diagnostics, multidisciplinary treatments, and prognosis of the most common bone sarcomas of childhood and adolescence—osteosarcoma and Ewing sarcoma. Both have their peak incidence among teenagers; both carry a high risk of metastatic spread. Local therapy alone is therefore rarely curative. Combining local therapies with intensive multidrug chemotherapy, usually employed both before and afterwards, can lead to long-term disease-free survival in approximately two thirds of affected young patients. Bone sarcomas should only be treated by experienced centres able to provide access to the full spectrum of required expert care. This includes access to essential diagnostic methods such as conventional radiography and magnetic resonance imaging (MRI) for evaluation of the primary, computed tomography (CT) of the chest to search for lung metastases, and radionuclide bone scan, positron emission tomography/computed tomography (PET/CT) and/or whole-body MRI to search for bone metastases. Local treatment of osteosarcoma is surgery whenever feasible. Limb-saving resections have largely replaced amputations. There is also a trend towards surgery in Ewing sarcoma, where radiotherapy has traditionally held a larger role. Histological response of the primary to preoperative chemotherapy is an important prognostic factor in both malignancies. Attempts to improve the prognosis of poor responders by postoperative treatment modifications have failed in osteosarcoma, but may work to some extent in Ewing sarcoma. Unfortunately, the many recent advances in the knowledge about their tumour biology have not yet resulted in better treatments for either of these two most common bone sarcomas of childhood and adolescence.
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Conference papers on the topic "Cancer chemotherapy; Intelligent search"

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Su, Yifan, Dehui Li, Huanfang Fan, and Chunxia Sun. "Compound Kushen Injection combined with Chemotherapy in Advanced Gastric Cancer." In IMIP 2020: 2020 2nd International Conference on Intelligent Medicine and Image Processing. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3399637.3399653.

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Beduk, Hediye, Mehmet Seckin Beduk, Ahmet Dirican, and M. Ibrahim Tuglu. "Estimating Chemotherapy Side Effect in Histopathologically Diagnosed Patients Over 65 With Metastatic Breast Cancer Using Deep Learning." In 2019 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, 2019. http://dx.doi.org/10.1109/asyu48272.2019.8946443.

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Maiti, Ritabrata, Priyanka Agarwal, Ragyayee Ravinder Kumar, and Aruna Bhat. "Detection Of Skin Cancer Using Neural Architecture Search with Model Quantization." In 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2021. http://dx.doi.org/10.1109/iciccs51141.2021.9432190.

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Alagarsamy, Saravanan, R. Raja Subramanian, Theepika Shree, Soundarya kannan, Mounika Balasubramanian, and Vishnuvarthanan Govindaraj. "Prediction of Lung Cancer using Meta-Heuristic based Optimization Technique: Crow Search Technique." In 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS). IEEE, 2021. http://dx.doi.org/10.1109/icccis51004.2021.9397199.

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Ruan, Xiaogang, Jinlian Wang, and Hui Li. "An Intelligent Search Algorithm for Feature Gene Selection of Chinese Gastric Cancer with mRNA Microarray Data." In 2007 1st International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icbbe.2007.63.

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Uetake, Hiroyuki, Toshiaki Ishikawa, Megimi Ishiguro, Kenta Murotani, Shigeyuki Matsui, and Kenichi Sugihara. "Abstract 4684: Biomarker search using gene expression databases in a phase III, controlled clinical trial (ACTS-CC) of postoperative adjuvant chemotherapy for stage III colon cancer: Results of cluster analysis." In Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC. American Association for Cancer Research, 2013. http://dx.doi.org/10.1158/1538-7445.am2013-4684.

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Malmström, A., H. Green, K. Bachmeier, L. Carlsson, J. Hansen, M. Lagerlund, B. Norberg, Å. Franzén, and A. Åleskog. "Abstract P6-11-07: A Phase IV Trial of Caelyx as First Line Chemotherapy (CT) in Women 65 Years or Older with Locally Advanced or Metastatic Breast Cancer: In Search for Treatment Predictive Factors." In Abstracts: Thirty-Third Annual CTRC‐AACR San Antonio Breast Cancer Symposium‐‐ Dec 8‐12, 2010; San Antonio, TX. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/0008-5472.sabcs10-p6-11-07.

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Uetake, Hiroyuki, Toshiaki Ishikawa, Megimi Ishiguro, and Shigeyuki Matsui. "Abstract CT211: Biomarker search using gene expression databases in a phase III controlled clinical trial of postoperative adjuvant chemotherapy for stage III colon cancer (ACTS-CC): correlation between clinicopathological factors and gene expression level." In Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.am2015-ct211.

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Uetake, Hiroyuki, Toshiaki Ishikawa, Megimi Ishiguro, Shigeyuki Matsui, and Kenichi Sugihara. "Abstract 283: Biomarker search using gene expression databases in a phase III, controlled clinical trial of postoperative adjuvant chemotherapy for stage III colon cancer (acts-cc): Correlation between gene expression and DNA copy number." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-283.

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