Relevant bibliographies by topics / Intelligent methods of diagnosis

Contents

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

Academic literature on the topic 'Intelligent methods of diagnosis'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Intelligent methods of diagnosis"

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Wang, Huaqing, Peng Chen, and Shuming Wang. "Intelligent diagnosis methods for plant machinery." Frontiers of Mechanical Engineering in China 5, no. 1 (2009): 118–24. http://dx.doi.org/10.1007/s11465-009-0084-z.

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Zhu, Yong, Qingyi Wu, Shengnan Tang, Boo Cheong Khoo, and Zhengxi Chang. "Intelligent Fault Diagnosis Methods for Hydraulic Piston Pumps: A Review." Journal of Marine Science and Engineering 11, no. 8 (2023): 1609. http://dx.doi.org/10.3390/jmse11081609.

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As the modern industry rapidly advances toward digitalization, networking, and intelligence, intelligent fault diagnosis technology has become a necessary measure to ensure the safe and stable operation of mechanical equipment and effectively avoid major disaster accidents and huge economic losses caused by mechanical equipment failure. As the “power heart” of hydraulic transmission systems, hydraulic piston pumps (HPPs) occupy an important position in aerospace, navigation, national defense, industry, and many other high-tech fields due to their high-rated pressure, compact structure, high ef
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Wei-Fang Li, Wei-Fang Li, Hai-Xin You Wei-Fang Li, and Xiao-Yu Guo Hai-Xin You. "Intelligent Diagnosis Method for Orthopedic Diseases Based on Medical Images." 電腦學刊 34, no. 5 (2023): 205–12. http://dx.doi.org/10.53106/199115992023103405016.

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<p>This article proposes an orthopedic image recognition method based on an improved convolutional neural network to address the traditional diagnostic methods of orthopedic diseases and the diverse types of orthopedic diseases in the diagnostic process. This method uses a fixed convolutional number to extract key features of orthopedic diseases and reduce the number of features. The article takes the diagnosis of gout in bone diseases as an example and designs an evaluation method based on visualization technology and quantitative indicator calculation. The quantitative indicator calcul
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Lyfar, Volodymyr, Olena Lyfar, and Volodymyr Zynchenko. "METHODS OF INTELLIGENT DATA ANALYSIS USING NEURAL NETWORKS IN DIAGNOSIS." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 14, no. 2 (2024): 109–12. http://dx.doi.org/10.35784/iapgos.5746.

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The considered methods make it possible to develop the structure of diagnostic systems based on neural networks and implement decision support systems in classification diagnostic problems. The study uses general special methods of data mining and the principles of constructing an artificial intelligence system based on neural networks. The problems that arise when filling knowledge bases and training neural networks are highlighted. Methods for developing models of intelligent data processing for diagnostic purposes based on neural networks are proposed. The authors developed and verified an
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Arad, Fereshteh, Seyyed Mohammad Mousavi, Soodeh Hosseini, Maryam Amizade, and Ayyub Sheikhi. "Intelligent Diagnosis of Larynx Cancer Using Machine Learning Methods." Journal of Health and Biomedical Informatics 11, no. 2 (2024): 115–30. https://doi.org/10.34172/jhbmi.2024.18.

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Introduction: Larynx cancer can be benign or malignant based on various factors. This research aimed to provide a machine learning -based model to improve the diagnosis of individuals with larynx cancer . Method: In the first step, the voices of the people who visited the medical centers (including the sounds (A), (E), and (O)) were recorded and considered as a data set. In the second step, the data were classified into three classes (benign cancer, malignant cancer, and healthy) by a specialist. In the third step, the data cleaning was done. In the fourth step, the features related to sound w
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Shi, Rong Bo, Zhi Ping Guo, and Zhi Yong Song. "Research Based on State Monitoring of CNC Machine Tools Intelligent Security System." Applied Mechanics and Materials 427-429 (September 2013): 1328–32. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1328.

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Analyse the cause of fault in CNC Machine, research the corresponding solve scheme, and to realize the state can monitor equipment operation, improve equipment reliability, the development set of machine condition monitoring, fault warning, fault diagnosis and troubleshooting as one of the intelligent security system. Based on the CNC machine intelligence support system research, design, introduces the key technologies and methods. Screw lift state of motion monitoring, for example, trend analysis exercise state, intelligent fault diagnosis, in order to achieve protection of the intelligent CN
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Hu, Hao, and Ying Min Yan. "Fault Diagnosis Technology of Equipment System." Applied Mechanics and Materials 380-384 (August 2013): 1003–8. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1003.

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With the development of computer technology, the development of artificial intelligence technology, diagnostic techniques to change rapidly in the intelligent stage of development, this paper will mainly based on artificial intelligent fault diagnosis methods are described, mainly the application of BP network in fault diagnosis. And application principle to design a user-friendly display system. Make diagnosis data clearly show on the panel, and at the same time show the fault type and other necessary data. Then the bus data tracking, were analyzed. The system for a new system has complex lin
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Li, Zhi. "Overview of the faults and diagnosis methods of the hydraulic system of modern coal mining machines." E3S Web of Conferences 528 (2024): 02019. http://dx.doi.org/10.1051/e3sconf/202452802019.

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The high power, high efficiency, low failure rate, and intelligence of coal mining equipment are important directions for the development of coal mining machines both domestically and internationally. The implementation of efficient and low failure coal mine equipment is an important prerequisite for ensuring the smooth deployment of intelligent mines. At present, coal mining equipment generally consists of three parts: mechanical, electrical, and hydraulic. However, hydraulic pressure is a necessary system for coal mining equipment to complete high-power and intelligent operations. This artic
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Feng, Ying, and Yongqin Wang. "Intelligent Diagnostic System Development based on Artificial Intelligence Technology." Frontiers in Computing and Intelligent Systems 5, no. 3 (2023): 8–13. http://dx.doi.org/10.54097/fcis.v5i3.13814.

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Intelligent diagnosis is an important scenario in smart healthcare, with conversational diagnostic scenarios being the most common. The process of collecting symptom information through conversations with users and inferring diseases based on symptoms. Through a dialogue based diagnostic system, it can meet some of the medical consultation needs of residents, thereby freeing doctors from some basic consultations and greatly alleviating the shortage of medical resources. In the actual diagnosis process, the symptoms reported by patients are often insufficient to support accurate diagnosis. It i
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Huang, Xiaoge, Yiyi Zhang, Jiefeng Liu, Hanbo Zheng, and Ke Wang. "A Novel Fault Diagnosis System on Polymer Insulation of Power Transformers Based on 3-stage GA–SA–SVM OFC Selection and ABC–SVM Classifier." Polymers 10, no. 10 (2018): 1096. http://dx.doi.org/10.3390/polym10101096.

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Dissolved gas analysis (DGA) has been widely used in various scenarios of power transformers’ online monitoring and diagnoses. However, the diagnostic accuracy of traditional DGA methods still leaves much room for improvement. In this context, numerous new DGA diagnostic models that combine artificial intelligence with traditional methods have emerged. In this paper, a new DGA artificial intelligent diagnostic system is proposed. There are two modules that make up the diagnosis system. The two modules are the optimal feature combination (OFC) selection module based on 3-stage GA–SA–SVM and the
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Dissertations / Theses on the topic "Intelligent methods of diagnosis"

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Liu, Haoran. "Statistical and intelligent methods for default diagnosis and loacalization in a continuous tubular reactor." Phd thesis, INSA de Rouen, 2009. http://tel.archives-ouvertes.fr/tel-00560886.

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The aim is to study a continuous chemical process, and then analyze the hold process of the reactor and build the models which could be trained to realize the fault diagnosis and localization in the process. An experimental system has been built to be the research base. That includes experiment part and record system. To the diagnosis and localization methods, the work presented the methods with the data-based approach, mainly the Bayesian network and RBF network based on GAAPA (Genetic Algorithm with Auto-adapted of Partial Adjustment). The data collected from the experimental system are used
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Guo, Ran. "Intelligent method for collecting vital signals in versatile distributed e-home healthcare." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691807.

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Vétil, Rebeca. "Artificial Intelligence Methods to Assist the Diagnosis of Pancreatic Diseases in Radiology." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT014.

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Avec l’augmentation de son incidence et son taux de survie à cinq ans (9%), le cancer du pancréas pourrait devenir la troisième cause de décès par cancer d’ici 2025.Ces chiffres sont notamment dus aux diagnostics tardifs, limitant les options thérapeutiques. Cette thèse vise à assister les radiologues dans le diagnostic du cancer du pancréas sur des images scanner grâce à des outils d’intelligence artificielle (IA) qui faciliteraient un diagnostic précoce. Pour atteindre ces objectifs, trois pistes de recherche ont été explorées. Premièrement, une méthode de segmentation automatique du pancréa
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Herrera, Liana J. Marmol. "Artificial intelligence methods for the diagnosis of myocardial damage in Chagas' disease using electrocardiographic signals." Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314320.

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Bezha, Minella. "Development of deterioration diagnostic methods for secondary batteries used in industrial applications by means of artificial intelligence." Thesis, https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB13127438/?lang=0, 2020. https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB13127438/?lang=0.

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蓄電池は携帯機器，電気自動車をはじめ，自然エネルギー有効利用に至るまで広範囲に利用され，その重要性はますます高まっている。これら機器の使用時間や特性は蓄電池の特性に大きく依存することから，電池自体の特性改善に加え，劣化を診断してより効率的に電池を運用することが求められている。本論文は，非線形情報処理を得意とする人工知能を用いた2次電池の劣化診断法を開発し，エネルギーの有効利用に資する技術を確立した。機器動作時の電池電圧・電流波形と電池劣化特性との関連性を，人工知能を用い学習することにより，機器稼働時に電池の劣化を診断することができる。なお，この関連性は非線形で複雑であるが，非線形分析を得意とする人工知能は劣化診断に適している。学習には時間を要するものの，診断は短時間になし得ることから，提案法は稼働時劣化診断に適している。本論文では，この特徴を生かし，電池の等価回路（ECM）を導出し，充電率（SOC），容量維持率（SOH）を推定している。また，本論文では現在産業応用分野で用いられている，リチウムイオン電池，ニッケル水素電池，鉛蓄電池を対象とし，提案法はあらゆる電池使用機器に応用可能である。また，提案法を電池状態監視装置（BMU）や，マイコンなどを用いた組み込みシステムに応用可能とし，実証している。以上のことから，本論文は，新たな蓄電池の劣化診断法の確立し，その有効性を確認している。<
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Pous, i. Sabadí Carles. "Case based reasoning as an extension of fault dictionary methods for linear electronic analog circuits diagnosis." Doctoral thesis, Universitat de Girona, 2004. http://hdl.handle.net/10803/7728.

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El test de circuits és una fase del procés de producció que cada vegada pren més importància quan es desenvolupa un nou producte. Les tècniques de test i diagnosi per a circuits digitals han estat desenvolupades i automatitzades amb èxit, mentre que aquest no és encara el cas dels circuits analògics. D'entre tots els mètodes proposats per diagnosticar circuits analògics els més utilitzats són els diccionaris de falles. En aquesta tesi se'n descriuen alguns, tot analitzant-ne els seus avantatges i inconvenients.<br/>Durant aquests últims anys, les tècniques d'Intel·ligència Artificial han esde
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Behroozinia, Pooya. "Finite Element Analysis of Defects in Cord-Rubber Composites and Hyperelastic Materials." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/87703.

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In recent years, composite materials have been widely used in several applications due to their superior mechanical properties including high strength, high stiffness, and low density. Despite the remarkable advancements in theoretical and computational methods for analyzing composites, investigating the effect of lamina properties and lay-up configurations on the strength of composites still remains an active field of research. Finite Element Method (FEM) and Extended Finite Element Method (XFEM) are powerful tools for solving the boundary value problems. One of the objectives of this work is
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Juuso, E. (Esko). "Integration of intelligent systems in development of smart adaptive systems:linguistic equation approach." Doctoral thesis, Oulun yliopisto, 2013. http://urn.fi/urn:isbn:9789526202891.

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Abstract Smart adaptive systems provide advanced tools for monitoring, control, diagnostics and management of nonlinear multivariate processes. Data mining with a multitude of methodologies is a good basis for the integration of intelligent systems. Small, specialised systems have a large number of feasible solutions, but highly complex systems require domain expertise and more compact approaches at the basic level. Linguistic equation (LE) approach originating from fuzzy logic is an efficient technique for these problems. This research is focused on the smart adaptive applications, where diff
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Bishop, James. "The Potential of Misdiagnosis of High IQ Youth by Practicing Mental Health Professionals: A Mixed Methods Study." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1062851/.

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The difficulty of distinguishing between genuine disorder and characteristics that can be attributed to high IQ increases the likelihood of diagnostic error by mental health practitioners. This mixed methods study explores the possibility of misdiagnosis of high IQ youth by mental health professionals. Participants were private practice mental health professionals who read case study vignettes illustrating high IQ youth exhibiting characteristics associated with their population. Participants then completed a survey and provided an assessment of the hypothetical client. In the study, 59% of pa
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Ващенко, Ярослав Васильович. "Удосконалення технології діагностування стану тягового асинхронного електроприводу рухомого складу". Thesis, Український державний університет залізничного транспорту, 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/22714.

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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.22.09 – електротранспорт. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2016 р. Дисертація присвячена вирішенню науково-технічної задачі по удосконаленню технології діагностування стану тягового асинхронного електроприводу рухомого складу на основі застосування діагностичних ознак, що свідчили б про настання аварійних режимів, а також розробці технологій, методів та алгоритмів, що дозволили б виявляти та упереджувати подальший розвиток таких режимів. Для виконання дослід
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Books on the topic "Intelligent methods of diagnosis"

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Aldrich, Chris. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer London, 2013.

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Raza, Khalid, ed. Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8534-0.

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Gerald, Schaefer, Hassanien Aboul Ella, and Jiang J. Ph D, eds. Computational intelligence in medical imaging techniques and applications. Chapman & Hall/CRC, 2008.

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Ashlesha, Jain, ed. Artificial intelligence techniques in breast cancer diagnosis and prognosis. World Scientific, 2000.

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Olivier, Haas, and Burnham Keith J, eds. Intelligent and adaptive systems in medicine. Taylor & Francis, 2008.

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Hatzilygeroudis, Ioannis, Vasile Palade, and Jim Prentzas, eds. Advances in Combining Intelligent Methods. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46200-4.

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Yager, Ronald R., Marek Z. Reformat, and Naif Alajlan, eds. Intelligent Methods for Cyber Warfare. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08624-8.

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Segovia, Javier, Piotr S. Szczepaniak, and Marian Niedzwiedzinski, eds. E-Commerce and Intelligent Methods. Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1779-9.

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1963-, Segovia Javier, Szczepaniak Piotr S. 1953, and Niedzwiedzinski Marian 1947-, eds. E-commerce and intelligent methods. Physica-Verlag, 2002.

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Tzafestas, Spyros G., ed. Methods and Applications of Intelligent Control. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5498-7.

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Book chapters on the topic "Intelligent methods of diagnosis"

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Liu, Min, Ling Li, and Feng Yan. "Data-Driven Fault Diagnosis Methods." In Intelligent Predictive Maintenance. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2677-6_7.

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Liu, Min, Ling Li, and Feng Yan. "Methods of Fault Diagnosis and Prediction." In Intelligent Predictive Maintenance. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2677-6_2.

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Li, Weihua, Xiaoli Zhang, and Ruqiang Yan. "Supervised SVM Based Intelligent Fault Diagnosis Methods." In Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3537-6_2.

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Peng, Hong, and Jun Wang. "Fault Diagnosis." In Computational Intelligence Methods and Applications. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5280-5_8.

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Shree, Ramya, Suraj Madagaonkar, Lakshmi Aashish Prateek, et al. "Application of Ensemble Methods in Medical Diagnosis." In Advances in Intelligent Systems and Computing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0550-8_29.

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Li, Weihua, Xiaoli Zhang, and Ruqiang Yan. "Semi-supervised Learning Based Intelligent Fault Diagnosis Methods." In Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3537-6_3.

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Ramya, R., A. Siva Sakthi, R. Rajalakshmi, and M. Preethi. "Healthcare Technologies Serving Cancer Diagnosis and Treatment." In Translating Healthcare Through Intelligent Computational Methods. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27700-9_18.

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Muthulakshmi, Lakshmanan, Josephine Selle Jeyanathan, Shalini Mohan, R. P. Suryasankar, D. Devaraj, and Nellaiah Hariharan. "Technologies and Therapies for Disease Diagnosis and Treatment." In Translating Healthcare Through Intelligent Computational Methods. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27700-9_11.

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Poovizhi, P., J. Shanthini, R. M. Bhavadharini, S. Karthik, and Anand Paul. "Therapy and Diagnosis of Cancer Techniques: A Review." In Translating Healthcare Through Intelligent Computational Methods. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27700-9_19.

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Wang, Jing, Jinglin Zhou, and Xiaolu Chen. "Simulation Platform for Fault Diagnosis." In Intelligent Control and Learning Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8044-1_4.

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AbstractThe previous chapters have described the mathematical principles and algorithms of multivariate statistical methods, as well as the monitoring processes when used for fault diagnosis. In order to validate the effectiveness of data-driven multivariate statistical analysis methods in the field of fault diagnosis, it is necessary to conduct the corresponding fault monitoring experiments. Therefore this chapter introduces two kinds of simulation platform, Tennessee Eastman (TE) process simulation system and fed-batch Penicillin Fermentation Process simulation system. They are widely used a
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Conference papers on the topic "Intelligent methods of diagnosis"

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Montasser, Reem Kadry, Sherif A. Mazen, and Iman M. A. Helal. "From Data to Diagnosis: Investigating Approaches in Mental Illness Detection." In 2024 Intelligent Methods, Systems, and Applications (IMSA). IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652870.

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Darwish, Esraa, Wafaa Abdelgawad, Marwan Makhlouf, et al. "A Mobile-Based Deep Learning System for Skin Disease Diagnosis." In 2024 Intelligent Methods, Systems, and Applications (IMSA). IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652699.

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Tarek, Hanan, Nada Khaled, Youanna Aziz, et al. "AI-Driven Approach for Diagnosis and Treatment Selection for Hepatocellular Carcinoma." In 2024 Intelligent Methods, Systems, and Applications (IMSA). IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652786.

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Al Tawil, Arar, Ibrahim A. Gomaa, Magdy Abd-Elghany Zeid, et al. "Optimizing ASD Diagnosis: Enhanced Autism Spectrum Disorder Prediction Using Machine Learning Classifiers." In 2024 Intelligent Methods, Systems, and Applications (IMSA). IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652789.

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Linda, Bellal, Khemis Kamila, Bendjillali Ridha Ilyas, Kherraf Yamina, Borsali Leila, and Bendelhoum Mohammed Sofiane. "Enhancing Thyroid Cancer Diagnosis with Advanced Deep Learning Methods." In 2024 International Conference on Telecommunications and Intelligent Systems (ICTIS). IEEE, 2024. https://doi.org/10.1109/ictis62692.2024.10894666.

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Liu, Renhao, Longlong Yang, Yuan Feng, and Chang Liu. "Research on fuzzy fault diagnosis methods for high-power servo systems." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039857.

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Xiaoyi, Ye, and Lee Sui Ping. "Machine Learning Methods for Breast Cancer Diagnosis." In 2024 International Conference on Computing Innovation, Intelligence, Technologies and Education (CIITE). IEEE, 2024. https://doi.org/10.1109/ciite62244.2024.10987661.

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R, Sridevi, Helen K. Joy, Karthikeyan K. J, Gopika S. S, Neha Seirah Biju, and Shriniha PA. "Employing Artificial Intelligence Methods for the Diagnosis of Autism Spectrum Disorder in Children." In 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS). IEEE, 2024. https://doi.org/10.1109/icicnis64247.2024.10823377.

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Appavu, Narenthirakumar. "Oral Cancer Histopathological Detection and Diagnosis Using Hybrid AI Deep Learning Methods." In 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2025. https://doi.org/10.1109/idciot64235.2025.10915019.

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Fabian, Bianca Antonia, and Cristian-Cosmin Vancea. "Efficient Methods for Improving Brain Tumors Diagnosis in MRI Scans Using Deep Learning." In 2024 IEEE 20th International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2024. https://doi.org/10.1109/iccp63557.2024.10793036.

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Reports on the topic "Intelligent methods of diagnosis"

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WANG, MIN, Sheng Chen, Changqing Zhong, et al. Diagnosis using artificial intelligence based on the endocytoscopic observation of the gastrointestinal tumours: a systematic review and meta-analysis. InPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.2.0096.

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Review question / Objective: With the development of endoscopic techniques, several diagnostic endoscopy methods are available for the diagnosis of malignant lesions, including magnified pigmented endoscopy and narrow band imaging (NBI).The main goal of endoscopy is to achieve the real-time diagnostic evaluation of the tissue, allowing an accurate assessment comparable to histopathological diagnosis based on structural and cellular heterogeneity to significantly improve the diagnostic rate for cancerous tissues. Endocytoscopy (ECS) is based on ultrahigh magnification endoscopy and has been app
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Sokolov, Alexander. Modern Integrated Methods of Reagent-Free Liquid Treatment. Intellectual Archive, 2025. https://doi.org/10.32370/iaj.3262.

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The article presents a new approach to reagent-free liquid treatment systems based on resonance diagnostics and adaptive control technologies. The author discusses the integration of non-contact, sensor-based methods for monitoring the physicochemical parameters of liquids in real time, applicable in water purification, industrial processing, and environmental safety. The system described utilizes intelligent algorithms to detect impurities, adjust treatment protocols, and ensure high accuracy without chemical reagents.
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Alhasson, Haifa F., and Shuaa S. Alharbi. New Trends in image-based Diabetic Foot Ucler Diagnosis Using Machine Learning Approaches: A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0128.

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Review question / Objective: A significant amount of research has been conducted to detect and recognize diabetic foot ulcers (DFUs) using computer vision methods, but there are still a number of challenges. DFUs detection frameworks based on machine learning/deep learning lack systematic reviews. With Machine Learning (ML) and Deep learning (DL), you can improve care for individuals at risk for DFUs, identify and synthesize evidence about its use in interventional care and management of DFUs, and suggest future research directions. Information sources: A thorough search of electronic database
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Dumas, Nathalie, Flourentzou Flourentzos, Julien BOUTILLIER, Bernard Paule, and Tristan de KERCHOVE d’EXAERDE. Integration of smart building technologies costs and CO2 emissions within the framework of the new EPIQR-web application. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541616188.

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The EPIQR method was developed between 1996 and 1998 within the framework of the European research programme JOULE II and with the support of the Swiss Federal Office for Education and Science. In its first versions, the EPIQR software and EPIQR+ that succeeded it, were desktop tools, allowing a precise diagnosis of the state of deterioration of an existing building and the elaboration of renovation scenarios including the different costs of the necessary works. However, deep refurbishment rate is still low. Climatic emergency state declared by most of the Swiss Cantons makes it necessary to s
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5

Martinak, R., Anthony E. Kelly, D. Sleeman, J. Moore, and R. D. Ward. Diagnosis and Remediation in the Context of Intelligent Tutoring Systems. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada199024.

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MOSKALENKO, O. L., S. YU TERESHCHENKO, and E. V. KASPAROV. INTERNET ADDICTION: DIAGNOSIS CRITERIA AND METHODS. Science and Innovation Center Publishing House, 2022. http://dx.doi.org/10.12731/978-0-615-67340-0-2.

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This article presents a review of the literature and analyzes scientific studies on the prevalence of Internet addiction in different countries. The authors conducted a scientific search using the relevant keywords in the PubMed and Google Scholar search engines, in the Scopus, Web of Science, MedLine, The Cochrane Library, EMBASE, Global Health, CyberLeninka, RSCI and others databases.
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Izenson, M. G., P. H. Rothe, and G. B. Wallis. Diagnosis of condensation-induced waterhammer: Methods and background. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/6752266.

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Rinchik, E. M. Workshop on molecular methods for genetic diagnosis. Final technical report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/501564.

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9

Masrur, M. A., ZhiHang Chen, and Yi L. Murphey. Intelligent Diagnosis of Open and Short Circuit Faults in Electric Drive Inverters For Real-Time Applications. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada513126.

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Jesneck, Jonathan, and Joseph Lo. Modular Machine Learning Methods for Computer-Aided Diagnosis of Breast Cancer. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada430017.

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