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Relevant bibliographies by topics / Symptom recognition

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Academic literature on the topic 'Symptom recognition'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Symptom recognition"

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Swedo, Susan E., Marjorie Garvey, Lisa Snider, Charlotte Hamilton, and Henrietta L. Leonard. "The PANDAS Subgroup: Recognition and Treatment." CNS Spectrums 6, no. 5 (November 2001): 419–26. http://dx.doi.org/10.1017/s1092852900021799.

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AbstractA subgroup of patients with childhood-onset obsessive-compulsive disorder (OCD) has been identified who share a common clinical course characterized by dramatic symptom exacerbations following Group A beta-hemolytic streptococcal (GABHS) infections. The term PANDAS has been applied to the subgroup, to indicate the postulated etiology of their symptoms: Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal infections. Five clinical characteristics define the PANDAS subgroup: presence of OCD and/or tic disorder, prepubertal symptom onset, sudden onset or abrupt exacerbations (sawtooth course), association with neurological abnormalities (presence of adventitious movements or motoric hyperactivity during exacerbations), and temporal association between symptom exacerbations and GABHS infections. Post-streptococcal symptom exacerbations are typically quite dramatic, with patients reporting that their symptoms “…came on overnight” or “…appeared all of a sudden a few days after I had a sore throat.” The post-streptococcal inflammatory nature of the neuropsychiatric symptoms provides novel opportunities for treatment and prevention, including immunomodulatory therapies such as therapeutic plasma exchange (TPE) and intravenous immunoglobulin (IVIG). A recently completed placebo-controlled trial revealed that both IVIG and TPE were effective in reducing neuropsychiatric symptom severity (40% to 55% reductions, respectively) for a group of severely ill children with OCD and/or tic disorders. Further research is required to determine why the treatments are helpful, as well as to ascertain whether or not antibiotic prophylaxis can help prevent post-streptococcal symptom exacerbations.

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White, Megan M., Jill Howie-Esquivel, and Mary A. Caldwell. "Improving Heart Failure Symptom Recognition." Journal of Cardiovascular Nursing 25, no. 1 (January 2010): 7–12. http://dx.doi.org/10.1097/jcn.0b013e3181b7af9e.

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Luan, Shenghua, Yujia Yang, Yuqi Huang, and Michelle McDowell. "Public knowledge of stroke and heart attack symptoms in China: a cross-sectional survey." BMJ Open 11, no. 1 (January 2021): e043220. http://dx.doi.org/10.1136/bmjopen-2020-043220.

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ObjectiveStroke and ischaemic heart disease have become the leading causes of death in China. We evaluated recognition of stroke and heart attack symptoms and stroke treatment-seeking behaviour in a large representative sample of the Chinese adult population and explored characteristics associated with recognition rates.DesignCross-sectional survey.SettingHousehold interviews.Participant3051 Chinese adults aged between 18 and 69 (50.7% female) were interviewed between January and March 2019.Primary and secondary outcome measuresPrimary measures include recognitions of stroke and heart attack symptoms and stroke treatment-seeking behaviour. Secondary measures include numeracy level, sociodemographics and prior history of cardiovascular diseases and high blood pressure.ResultsParticipants on average recognised 5.2 out of 14 stroke symptoms and 2.6 out of 6 heart attack symptoms. In the presence of stroke symptoms, three quarters of participants would take immediate action and call an ambulance, yet the second most common action was to advise the person to see a doctor (59%) rather than to consult a doctor immediately (34%). Recognition of atypical heartattack symptoms, such as nausea and feeling of anxiety, was poor. Symptom recognition rates were higher in females, people with a personal or family/friend history of cardiovascular events, those with higher numeracy scores, and for stroke symptoms, participants with high (versus low) education level. Furthermore, symptom recognition rate was negatively correlated with burden of cardiovascular diseases across the four economic regions of China.ConclusionRecognition of stroke and heart-attack symptoms was moderate and there remains a gap between recognising symptoms and taking immediate action. Interventions focusing on simple symptom detection tools and on building numerical competencies may help reduce the burden of cardiovascular diseases in China.

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LITHELL, M., C. BACKMAN, and Å. NYSTRÖM. "Pattern Recognition In Post-Traumatic Cold Intolerance." Journal of Hand Surgery 22, no. 6 (December 1997): 783–87. http://dx.doi.org/10.1016/s0266-7681(97)80448-2.

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The subjective symptoms called “post-traumatic cold intolerance” were analysed in a study of 40 patients with a history of digital trauma (amputation, neurovascular laceration, or comminuted fracture requiring surgical reconstruction). The patients were individually interviewed to obtain detailed information about perception of each symptom as well as the pattern of symptoms of posttraumatic cold intolerance. The study confirmed the high incidence of the condition and its potentially disabling nature. Although the individual symptoms described by the patients have a limited number of categories, the subjective expression of cold intolerance is too varied to allow an adequate definition or assessment to be based on any single symptom or group of symptoms.

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Tran, Phoebe, and Lam Tran. "Stroke and Heart Attack Symptom Recognition in Older US Adults by Cognitive Impairment Status." Neuroepidemiology 55, no. 3 (2021): 245–52. http://dx.doi.org/10.1159/000516343.

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<b><i>Introduction:</i></b> Cognitive impairment may make stroke and heart attack symptom recognition difficult, potentially resulting in treatment delays for those with these cardiovascular diseases (CVDs). Despite cognitive impairment affecting large numbers of older US adults who are also at increased risk of stroke and heart attack, little is known about stroke and heart attack symptom recognition in this population. As a result, this study sought to determine the impact of cognitive impairment on stroke and heart attack symptom recognition among older US adults. <b><i>Methods:</i></b> Using the 2014 and 2017 National Health Interview Surveys, we compared stroke and heart attack symptom recognition levels in US adults aged ≥65 years with cognitive impairment and those without cognitive impairment. Estimates of stroke and heart attack symptom recognition adjusted for CVD-related factors were assessed by cognitive impairment status. We also conducted analyses stratified by living arrangement and stroke and heart attack history for individuals with and without cognitive impairment. <b><i>Results:</i></b> US adults aged ≥65 years with cognitive impairment were observed to be 3.0–6.7% and 1.6–4.9%, respectively, less likely to recognize an individual stroke and heart attack symptom than similarly aged individuals without cognitive impairment. Recognition of all 5 stroke/heart attack symptoms was also lower among those with cognitive impairment, with this group being 9.7% less likely to recognize all stroke symptoms and 6.7% less likely to recognize all 5 heart attack symptoms compared to people without cognitive impairment. Following adjustment, individuals with cognitive impairment continued to have slightly lower recognition of certain individual stroke and heart attack symptoms as well as of all 5 symptoms of these conditions (stroke OR: 0.70 [95% CI: 0.58–0.85]; heart attack OR: 0.88 [95% CI: 0.75, 1.03]) than those without cognitive impairment. For individuals with cognitive impairment, living with others was linked with slightly better recognition of all individual stroke symptoms and heart attack history with better recognition of all individual heart attack symptoms. <b><i>Conclusions:</i></b> Additional work is needed to address the challenge of improving recognition levels for specific stroke and heart attack symptoms in older US adults with cognitive impairment and especially for members of this group who live alone.

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Selekman, Janice, and Eileen Malloy. "Difficulties in symptom recognition in infants." Journal of Pediatric Nursing 10, no. 2 (April 1995): 89–92. http://dx.doi.org/10.1016/s0882-5963(05)80003-x.

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Hunt, Tamerah N. "Video Educational Intervention Improves Reporting of Concussion and Symptom Recognition." Athletic Training Education Journal 10, no. 1 (January 1, 2015): 65–74. http://dx.doi.org/10.4085/100165.

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Context Concussion management is potentially complicated by the lack of reporting due to poor educational intervention in youth athletics. Objective Determine if a concussion-education video developed for high school athletes will increase the reporting of concussive injuries and symptom recognition in this group. Design Cross-sectional, between groups. Setting Athletes participating in South Carolina interscholastic athletics. Patients or Other Participants High school athletes (N = 68; males n = 42; females n = 26; mean age = 14.78 ± 1.38 years) participated in this study. The athletes were randomly assigned into 2 groups: concussion education (n = 34) and control (n = 34). Main Outcome Measures Participants were administered a survey before and after watching a video about concussion incidence, symptoms, and reporting conditions (intervention group) or a nutrition video (control group). Total symptom score and survey items served as dependent variables. Examination of group differences was performed through χ2 analyses and repeated-measures analysis of variance (ANOVA) calculations in SPSS 19.0 (SPSS Inc, Chicago, IL). Significance levels were set a priori at .05. Results Of all participants, 70.5% (48/68) reported not knowing the signs and symptoms of concussion before the study, and 26.5% (n = 18) reported having had at least 1 prior concussion. A statistically significant difference existed between those reporting having vs. not having knowledge of the signs and symptoms of concussion on total symptom score at baseline (t1,66 = 2.17, P = .038). Repeated-measures ANOVA calculated a statistically significant difference for concussion symptom recognition before and after the intervention (F1,66 = 7.47, P = .008) Conclusions A large percentage of high school athletes do not know the signs and symptoms of concussion. After an educational video, participants' symptom knowledge and previous concussions reported increased. Education of those involved in athletics using a standardized tool may increase reporting and aid in the assessment and management of concussion in this population.

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Kempnich, Clare L., Sophie C. Andrews, Fiona Fisher, Dana Wong, Nellie Georgiou-Karistianis, and Julie C. Stout. "Emotion Recognition Correlates With Social-Neuropsychiatric Dysfunction in Huntington’s Disease." Journal of the International Neuropsychological Society 24, no. 5 (December 28, 2017): 417–23. http://dx.doi.org/10.1017/s1355617717001308.

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AbstractObjectives: People with Huntington’s disease (HD) experience poor social quality of life, relationship breakdown, and social withdrawal, which are mediated to some extent by socially debilitating neuropsychiatric symptoms, such as apathy and disinhibition. Social cognitive symptoms, such as impaired emotion recognition, also occur in HD, however, the extent of their association with these socially debilitating neuropsychiatric symptoms is unknown. Our study examined the relationship between emotion recognition and symptom ratings of apathy and disinhibition in HD. Methods: Thirty-two people with premanifest or symptomatic-HD completed Part 1 of The Awareness of Social Inference Test (TASIT), which is a facial emotion recognition task. In addition, we obtained severity ratings for apathy and disinhibition on the Frontal Systems Behavior Scale (FrSBe) from a close family member. Our analyses used motor symptom severity as a proxy for disease progression. Results: Emotion recognition performance was significantly associated with family-ratings of apathy, above and beyond their shared association with disease severity. We found a similar pattern for disinhibition ratings, which fell short of statistical significance. As expected, worse emotion recognition performance was correlated with higher severity in FrSBe symptom ratings. Conclusions: Our findings suggest that emotion recognition abilities relate to key socially debilitating neuropsychiatric symptoms in HD. Our results help to understand the functional significance of emotion recognition impairments in HD, and may have implications for the development of remediation programs aimed at improving patients’ social quality of life. (JINS, 2018, 24, 417–423)

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Bahr, Raymond D. "Prodromal Symptom Recognition of a Heart Attack." Critical Pathways in Cardiology: A Journal of Evidence-Based Medicine 1, no. 3 (September 2002): 194–206. http://dx.doi.org/10.1097/00132577-200209000-00006.

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Riegel, Barbara, Victoria Vaughan Dickson, Janette Cameron, Jerry C. Johnson, Stephen Bunker, Karen Page, and Linda Worrall-Carter. "Symptom Recognition in Elders With Heart Failure." Journal of Nursing Scholarship 42, no. 1 (March 2010): 92–100. http://dx.doi.org/10.1111/j.1547-5069.2010.01333.x.

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Dissertations / Theses on the topic "Symptom recognition"

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Kennedy, Michael G. "Relapse in Schizophrenia : the relationships among insight, symptom recognition, symptom self-management, and perceived effectiveness of symptom self-management at the time of hospitalization /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/7372.

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Hull, Carolyn M., and Carolyn M. Hull. "Assessing the Impact of a Transitional Care Program on Symptom Recognition and Self-care in Heart Failure Patients." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/622989.

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Background: Heart failure (HF) is a complex, costly and debilitating chronic health condition. Symptom recognition and self-care are crucial components of heart failure management; however, many HF patients struggle to perform these behaviors and skills at a proficient level. A transitional care program in the Southwest provides services to heart failure patients. A primary program aim is to help facilitate enhanced symptom recognition and self-care among heart failure patients. This project focuses on the assessment of the impact of such a transitional care program on HF patients' ability to perform symptom recognition and self-care. Methods: Demographic questionnaires were distributed to collect socioeconomic data and clinical characteristics of participants. A pre and post SCHFI survey was completed by participants, and analysis of data performed using a paired t-test. Results: The 15 participants were primarily Hispanic, elderly, and male. The majority of participants reported an annual income less than $10,000, lived in close proximity to the transitional care clinic, reported living with family and/or friends, and had at least one additional comorbidity. There was improvement in self-care maintenance scores following the initial transitional care encounter; however, participants did not achieve self-care adequacy in this domain. Participants also did not achieve self-care adequacy in self-management. Self-confidence scores improved to reach adequacy following the initial transitional care encounter; however, results were not statistically significant. Conclusion: With the complexities of HF self-management, it is not alarming that these patients have continued to struggle with symptom recognition and self-care. Recommendations are made for future research and interventions.

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Lim, Anita Wey Wey. "Investigating the potential for expediting diagnosis of ovarian cancer via prompt symptom recognition & "targeted screening"." Thesis, Queen Mary, University of London, 2009. http://qmro.qmul.ac.uk/xmlui/handle/123456789/500.

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This thesis explores the potential for using symptoms as a tool to bring forward the diagnosis of ovarian cancer. Current evidence supports the existence of prediagnostic symptoms, however symptom lead time has yet to be adequately quantified. „Targeted screening‟ is one possible approach to expediting diagnosis. This would involve offering a blood test (e.g. CA125 or a future biomarker) to postmenopausal women presenting to primary care with symptoms possibly related to ovarian cancer. Key barriers include the non-specific nature of ovarian cancer symptoms and potential impact on GP workload. The main aims of this PhD research project were: To quantify the lead time of symptoms in ovarian cancer. To estimate the GP workload associated with offering a blood test to postmenopausal women with ovarian cancer symptoms. Following a background to ovarian cancer symptoms research; a brief overview of the epidemiology of ovarian cancer, a case-control study to quantify symptom lead time, and a cross-sectional pilot study to estimate GP workload and symptom specificity in women aged 45-74 in the general population is presented. This is complemented by a systematic review focussed on the evidence for symptom lead time in ovarian cancer since 1980, with an update on ovarian cancer symptoms and a discussion of some of the methodological issues. The main findings showed that the diagnostic process could be initiated at least 3 months prior to the current date of diagnosis, in 45% to 74% of cases. However, pilot data suggest that 13%-35% of women in the general population aged ≥45 would be offered „targeted screening‟ in 1 year. Delays in ovarian cancer diagnosis of concern were identified but require further examination. Timing of symptoms is also an important consideration. The concluding chapter summarises the main findings of this thesis and discusses possibilities for future research.

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Walsh, Susan A. "The Effects of Pattern Recognition Based Simulation Scenarios on Symptom Recognition of Myocardial Infarction, Critical Thinking, Clinical Decision-Making, and Clinical Judgment in Nursing Students." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/nursing_diss/18.

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In the United States nearly 1 million annual new and recurrent myocardial infarctions (MI) occur with 10% of patients hospitalized with MI having unrecognized ischemic symptoms. Inexperienced nurses are expected to accurately interpret cardiac symptom cues, possibly without ever having experienced care of patients with MI, yet have been shown to be less able to classify symptom cues and reach accurate conclusions than experienced nurses. The purpose of this study was to test an educational intervention using theories of pattern recognition to develop CT in MI and improve nursing students’ clinical decision-making and clinical judgment using high fidelity patient simulation. This study used a quasi-experimental three group pre-/post-test design and qualitative data to triangulate information on critical thinking, clinical decision-making, and clinical judgment in MI. A sample of junior baccalaureate in nursing students (N = 54) from a large metropolitan university were divided in pairs and randomized to one of two control groups. Data were collected with instruments which measured pattern recognition in MI, critical thinking in MI, and self-perception of clinical decision-making. In addition, diagnostic efficiency and accuracy were measured. Triangulation on clinical decision making with semi-structured interviews using ‘thinking aloud’ technique was conducted. Data were analyzed as qualitative data and compared among groups. Students who were given prototypes for MI using simulation significantly improved critical thinking as measured by pattern recognition in MI (t(3.153(2), p = .038) compared with the non-simulation control group. Qualitative findings showed that students receiving the experimental simulation with a non-MI scenario and feedback-based debriefing had greatest gains in clinical reasoning which included development of clinical decision-making using analytic hypothetico-deductive and Bayesian reasoning processes and learned avoidance of heuristics. Students receiving the experimental simulation learned to identify salient symptom cues, analyzed data more complexly, and reflected on their simulation experience in a way which students reported improved learning. Students who were given MI only simulation scenarios developed deleterious heuristics and showed fewer gains in clinical reasoning, though both simulation groups demonstrated greater critical thinking ability than the non-simulation control group. Findings support the use of simulation to improve clinical reasoning including pattern recognition and clinical decision-making, and emphasize the significance of simulation scenario construction and debriefing to achieving learning outcomes. The findings could be used to guide further research to improve critical thinking, clinical decision-making, and clinical judgment in nursing students using simulation. Funding for this study was provided by the American Association of Critical Care Nurses and Philips Medical Systems and a testing grant from Elsevier, Assessment.

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Farmer, Caroline. "Understanding poor help-seeking rates for major depressive disorder." Thesis, University of Exeter, 2013. http://hdl.handle.net/10871/14620.

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The principal aim of this thesis was to further understanding of the factors influencing decisions to seek treatment for Major Depressive Disorder. A review of the literature (Chapter 2) revealed a number of factors associated with help-seeking for mental health disorders. However, there was no existing theoretical model of decisions to seek treatment for MDD, and there was limited understanding of the psychological and emotional processes involved in seeking treatment for depressive symptoms. In Study 1 (Chapter 3), a qualitative study explored participants’ accounts of seeking treatment for MDD, which resulted in the development of a theoretical model of help-seeking. This model highlighted the role of identity and goals in decisions to seek treatment for MDD. Subsequent studies in this thesis sought to test predictions made by this model. Study 2 (Chapter 4) explored the relationship between identity and goal conflict and depressed individuals’ acknowledgement of depressive symptoms and perceived need for treatment. Findings of this study suggested that greater identity conflict, but not goal, conflict was associated with reduced acknowledgement of depressive symptoms and less perceived need for treatment. Study 3 (Chapter 5) sought to replicate this relationship, and also tested the extent to which identity as a depressed person and socio-cognitive models of health behaviour could predict (i) intentions to seek treatment for depression and (ii) current treatment seeking. This study found that identity conflict was associated with reduced acknowledgement of depressive symptoms, but failed to replicate the relationship between identity conflict and perceived need for treatment for depression. However, greater identity as a depressed person was associated with both current treatment seeking and greater intentions to seek help. Analyses demonstrated that the Theory of Planned Behaviour and the Health Belief Model predicted current help-seeking and help-seeking intentions, but identity as a depressed person explained an additional significant proportion of the variance. A unified model, drawing on these two theories and incorporating identity was found to be the best fit in accounting for intentions to seek help for depression. The findings of Study 4 (Chapter 6) demonstrated that identity as a depressed person was also a significant predictor of prospective help-seeking behaviour for MDD. In this study, the majority of factors from the Theory of Planned Behaviour and Health Belief Model, extended to include identity, predicted help-seeking behaviour indirectly via intentions to seek help. However, intentions to seek help only predicted a small proportion of the variance in help-seeking behaviour, and the findings revealed that a subsample of factors, including identity, directly predicted help-seeking behaviour. The final study sought to use an online focus group to develop a measure of symptom avoidance in depressed individuals. This study faced methodological difficulties, and Chapter 7 reflects on the use of online focus groups to explore patient experiences of illness. The findings of this study highlighted participant experiences of using an online focus group method to discuss personal experiences of MDD, and this chapter provides specific guidance for other researchers planning to use this method in the context of health research. The implications of the findings of this thesis are discussed in Chapter 8, alongside recommendations for future help-seeking research.

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Tsanas, Athanasios. "Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning." Thesis, University of Oxford, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572585.

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This study focuses on the development of an objective, automated method to extract clinically useful information from sustained vowel phonations in the context of Parkinson’s disease (PD). The aim is twofold: (a) differentiate PD subjects from healthy controls, and (b) replicate the Unified Parkinson’s Disease Rating Scale (UPDRS) metric which provides a clinical impression of PD symptom severity. This metric spans the range 0 to 176, where 0 denotes a healthy person and 176 total disability. Currently, UPDRS assessment requires the physical presence of the subject in the clinic, is subjective relying on the clinical rater’s expertise, and logistically costly for national health systems. Hence, the practical frequency of symptom tracking is typically confined to once every several months, hindering recruitment for large-scale clinical trials and under-representing the true time scale of PD fluctuations. We develop a comprehensive framework to analyze speech signals by: (1) extracting novel, distinctive signal features, (2) using robust feature selection techniques to obtain a parsimonious subset of those features, and (3a) differentiating PD subjects from healthy controls, or (3b) determining UPDRS using powerful statistical machine learning tools. Towards this aim, we also investigate 10 existing fundamental frequency (F_0) estimation algorithms to determine the most useful algorithm for this application, and propose a novel ensemble F_0 estimation algorithm which leads to a 10% improvement in accuracy over the best individual approach. Moreover, we propose novel feature selection schemes which are shown to be very competitive against widely-used schemes which are more complex. We demonstrate that we can successfully differentiate PD subjects from healthy controls with 98.5% overall accuracy, and also provide rapid, objective, and remote replication of UPDRS assessment with clinically useful accuracy (approximately 2 UPDRS points from the clinicians’ estimates), using only simple, self-administered, and non-invasive speech tests. The findings of this study strongly support the use of speech signal analysis as an objective basis for practical clinical decision support tools in the context of PD assessment.

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Friedman, Karen Blanc Spiers Mary. "Are symptoms of postpartum depression associated with deficits in facial and auditory emotional recognition? /." Philadelphia, Pa. : Drexel University, 2008. http://hdl.handle.net/1860/2828.

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Horsley, John Robert. "Respiratory symptoms in the elderly and their clinical significance in the recognition of asthma." Thesis, University of Southampton, 1990. https://eprints.soton.ac.uk/421960/.

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Lee, Brian N. "Facial Expression Discrimination in Adults Experiencing Posttraumatic Stress Symptoms." TopSCHOLAR®, 2011. http://digitalcommons.wku.edu/theses/1123.

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The present study examined the impact of posttraumatic stress symptoms (PTSS) on adults’ ability to discriminate between various facial expressions of emotions. Additionally, the study examined whether individuals reporting PTSS exhibited an attentional bias toward threat-related facial expressions of emotions. The research design was a 2 (expression intensity) x 3 (emotional pairing) x 2 (PTSS group) mixed-model factorial design. Participants for the study were 89 undergraduates recruited from psychology courses at Western Kentucky University. Participants completed the Traumatic Stress Schedule to assess for prior exposure to traumatic events. A median split was used to divide the sample into two groups (i.e., low and high PTSS). Additionally, participants also completed a demographics questionnaire, the Impact of Events Scale-Revised, the Center for Epidemiological Studies Depression Scale, and the Depression Anxiety Stress Scales to assess for possible covariates. Then, participants completed the discrimination of facial expressions task and the dot probe position task. Results indicate that individuals experiencing high levels of PTSS have difficulty discriminating between threatening and non-threatening facial expressions of emotions; additionally, these individuals’ difficulty is exacerbated by comorbid levels of anxiety symptoms. Furthermore, results suggests these individuals focus attention on threatening facial expressions while avoiding expressions that may activate memories associated with the prior trauma. These findings have significant clinical implications, as clinicians could focus treatment on correcting these difficulties which should help promote more beneficial social interactions for these individuals experiencing high levels of PTSS. Additionally, these behavioral measures could be used to assess the effectiveness of treatment. Effective treatment should help alleviate these difficulties, which could be measured by improved performance on the discrimination of facial expressions task and the dot probe position task from baseline to post-treatment.

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Sink, Holli E. "Distinguishing Subtypes of Psychopathy in Youth based on Anxiety, Posttraumatic Stress Symptoms, and Emotion Recognition." Miami University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1279481371.

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Books on the topic "Symptom recognition"

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Boa, E. R. An illustrated guide to the state of health of trees: Recognition and interpretation of symptoms and damage. Rome: Food and Agriculture Organization of the United Nations, 2003.

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Stanghellini, Giovanni. Symptom as cypher. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198792062.003.0023.

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This chapter argues that the symptom-as-aletheia concept can be better explained in the light of Jaspers’ concept of ‘cypher’. Cyphers show what without them would remain implicit for us. Symptoms are a special category of cyphers: through them alterity, that is, the hidden yet operative (and perplexing) dimension of our existence, is made manifest. Like symptoms, cyphers are the contingent opportunity of recognition, of a possible encounter between the person and the encompassing dimension of her existence. The cypher must keep on an inexhaustible signification with which no definite interpretation is commensurate. Symptoms in the phenomenological–hermeneutic paradigm are anomalies, but not abnormal phenomena in a strict sense. Rather, they are what awakens one’s care for oneself. The symptom reflects and reveals alterity in oneself—in it, alterity becomes conspicuous. From the vantage offered by the symptom one can see oneself from another, often radically different and new, perspective.

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Fine, Perry G., and Matthew Kestenbaum. Clinical Processes and Symptom Management. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190456900.003.0003.

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This chapter describes what to do when a patient experiences severe anxiety and uncontrolled agitation that negatively affect care and the caregiving environment. Agitation and severe anxiety (panic) represent some of the few true emergency conditions in a hospice setting, so early recognition and prevention are critical. The discussion covers causes in depth, including psychosocial/spiritual and biomedical causes. The chapter details a tactical approach to evaluating and managing severe anxiety and agitation. An example of this is assessing if the patient has an organic brain syndrome due to advancing disease with either local or systemic manifestations and reviewing medications for adverse drug reactions. It then details appropriate processes of care, such as providing pharmacotherapy for acute and recurrent agitation.

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Waldmann, Carl, Neil Soni, and Andrew Rhodes. Neurological disorders. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199229581.003.0022.

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Agitation and confusion 360Status epilepticus 362Meningitis 364Intracerebral haemorrhage 366Subarachnoid haemorrhage 368Ischaemic stroke 370Guillain–Barre syndrome 372Myasthenia gravis 374ICU neuromuscular disorders 376Tetanus 378Botulism 380Neurorehabilitation 382Hyperthermias 384Agitation and confusion are common features in critical illness. Agitation is a symptom or sign of numerous acute and chronic disease states that include pain, anxiety and delirium. Agitation is present in around half of ICU patients, with 15% experiencing severe agitation. Confusion may also be chronic or acute and arise from an overlapping set of pathological processes that includes hypoxia, hypotension, hypoglycaemia and dementia. It is possible to be agitated and not confused, and vice versa. Recognition and treatment of the underlying condition is of utmost importance, rather than treating the symptoms alone....

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Kendell, Mary, and Margie Wentzel. Women’s Health. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190466268.003.0011.

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Although the hormonal changes that occur during menopause are the same for all women, the experience of menopause will be as unique as the woman herself. It will be modulated as much by the physiological changes that occur in her body as it will be by her cultural upbringing, thoughts and attitudes about this time in her life, and her current life stressors. Recognition of menopause as a unique experience for every woman is an essential component of an integrative approach to health care for this phase of life. Management and treatment options should include proactive anticipatory education, symptom screening, diet and lifestyle recommendations and, when necessary, pharmacotherapeutics. This chapter covers vasomotor symptoms, skin changes, breast health and breast cancer, genitourinary complaints, sexuality, and hormone replacement therapy.

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Lyons, Kelly E., and Rajesh Pahwa. Recognition and Treatment of Non-Motor Symptoms of Parkinson's Disease. Oxford University Press, 2011.

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Forsyth, Rob, and Richard Newton. Signs and symptoms. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198784449.003.0003.

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This chapter addresses the diagnostic approach to the patterns of symptoms and signs commonly seen in the paediatric neurology clinic. It encourages pattern recognition. The presentations considered are: altered mental state (agitation/confusion); motor disorders (exercise limitation and muscle pain; eye or facial movement abnormalities; the floppy infant; a funny gait; weakness; unsteadiness or falls; toe-walking; disordered sensation, numbness, pain, dysaesthesia; deafness, loss or disturbance of hearing or vision; paroxysmal disorders (funny turns, loss of awareness, epilepsy, headache, movement disorders); developmental delay, impairment or regression, school failure; speech disturbance; behaviour disorder; symptoms that might suggest a spinal disorder such as back pain, incontinence, or scoliosis; other skeletal abnormality including abnormal skull size or shape, foot deformity; sleep disturbance.

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Bissonnette, Bruno, and Bernard Dalens. Syndromes: Rapid Recognition and Perioperative Implications. McGraw-Hill Professional, 2006.

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Bruno, Bissonnette, ed. Syndromes: Rapid recognition and perioperative management. New York: McGraw-Hill, 2005.

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Bissonnette, Bruno, and Bernard Dalens. Syndromes: Rapid Recognition and Perioperative Implications. McGraw-Hill Professional, 2006.

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Book chapters on the topic "Symptom recognition"

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Mata, Jutta, Ronald Frank, and Gerd Gigerenzer. "Symptom Recognition of Heart Attack and Stroke." In Transparent Communication of Health Risks, 79–96. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4358-2_6.

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Holat, Pierre, Nadi Tomeh, Thierry Charnois, Delphine Battistelli, Marie-Christine Jaulent, and Jean-Philippe Métivier. "Weakly-Supervised Symptom Recognition for Rare Diseases in Biomedical Text." In Lecture Notes in Computer Science, 192–203. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46349-0_17.

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Meenaatchi, S. M., and K. Rajeswari. "Rational Against Irrational Causes of Symptom Recognition Using Data Taxonomy." In Intelligent Data Communication Technologies and Internet of Things, 583–91. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9509-7_47.

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Meletti, Stefano. "Emotion Recognition." In Neuropsychiatric Symptoms of Neurological Disease, 177–93. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-22159-5_11.

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Ma, Liangyu, Jin Ma, Yongguang Ma, and Bingshu Wang. "To Diagnose a Slight and Incipient Fault in a Power Plant Thermal System Based on Symptom Zoom Technology and Fuzzy Pattern Recognition Method." In Advances in Machine Learning and Cybernetics, 958–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11739685_100.

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Afonso, David, and João Miguel R. Sanches. "Detection of Carotid Plaque Symptoms Using Ultrasound Imaging." In Pattern Recognition and Image Analysis, 584–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_69.

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Seabra, José, Luís Mendes Pedro, José Fernandes e Fernandes, and João Sanches. "Ultrasound Plaque Enhanced Activity Index for Predicting Neurological Symptoms." In Pattern Recognition and Image Analysis, 184–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21257-4_23.

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Niksic, Maja, and Lindsay J. L. Forbes. "Awareness of Colorectal Cancer: Recognition of Symptoms and Risk Factors by Socio-demographic Characteristics." In Timely Diagnosis of Colorectal Cancer, 1–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65286-3_1.

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Lorenzi, Paolo, Rosario Rao, Giulio Romano, Ardian Kita, Martin Serpa, Federico Filesi, Matteo Bologna, Antonello Suppa, Alfredo Berardelli, and Fernanda Irrera. "Using Neural Networks for the Recognition of Specific Motion Symptoms of the Parkinson’s Disease." In Advances in Neural Networks, 123–31. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33747-0_12.

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El Massi, Ismail, Youssef Es-saady, Mostafa El Yassa, Driss Mammass, and Abdeslam Benazoun. "A Hybrid Combination of Multiple SVM Classifiers for Automatic Recognition of the Damages and Symptoms on Plant Leaves." In Lecture Notes in Computer Science, 40–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33618-3_5.

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Conference papers on the topic "Symptom recognition"

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Du, Dongmei, and Qing He. "Orbit Shape Automatic Recognition Based on Artificial Neural Network." In ASME 2005 Power Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pwr2005-50208.

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Abstract:

Orbit is a significant symptom in the fault diagnosis of rotating machine. The orbit is a 2-D image and can be described by moment invariants, the shape property of 2-D image, which is a description with translating-, rotating-, and scaling-invariants for 2-D image. The descriptive method of orbit image is investigated and an automatic orbit shape recognition based on artificial neural network (ANN) with moment invariants is proposed in this paper. The ANN of orbit shape recognition is trained by the training patterns generated by computer simulation for plenty of orbit shapes. It is shown that the trained ANN is of good recognition performance and generalization capability when applied to recognition of the measured orbits. This method can be used to the intelligent expert system of fault diagnosis to obtain automatically online orbit symptom in shafts vibration monitoring of turbine generator, which will improve the automatization of obtaining fault symptom and the automatic diagnosis in the expert system.

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Wang, Qi, and Lu Zeng. "Chinese symptom component recognition via bidirectional LSTM-CRF." In 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI ). IEEE, 2018. http://dx.doi.org/10.1109/icaci.2018.8377564.

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Hu, Yue-li, and Jing Liu. "Application of Semantic Network in Recognition of Skin Symptom." In Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007). IEEE, 2007. http://dx.doi.org/10.1109/fskd.2007.182.

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Li, Jeffery, Patrick Martin, Wendy Powley, Kirk Wilson, and Chris Craddock. "A Sensor-Based Approach to Symptom Recognition for Autonomic Systems." In 2009 Fifth International Conference on Autonomic and Autonomous Systems. IEEE, 2009. http://dx.doi.org/10.1109/icas.2009.29.

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Yang, Zhengyuan, Amanda Kay, Yuncheng Li, Wendi Cross, and Jiebo Luo. "Pose-based Body Language Recognition for Emotion and Psychiatric Symptom Interpretation." In 2020 25th International Conference on Pattern Recognition (ICPR). IEEE, 2021. http://dx.doi.org/10.1109/icpr48806.2021.9412591.

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Speyerer, J. K., and A. J. Zeller. "Managing supply networks: symptom recognition and diagnostic analysis with Web services." In 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the. IEEE, 2004. http://dx.doi.org/10.1109/hicss.2004.1265485.

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Deng, Yang, Dagang Li, Qiang Zhang, and Ying Shen. "Medical Big Data Mining: Joint Symptom Name Recognition and Severity Estimation." In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2020. http://dx.doi.org/10.1109/bibm49941.2020.9313543.

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Dong, Guimin, Lihua Cai, Debajyoti Datta, Shashwat Kumar, Laura E. Barnes, and Mehdi Boukhechba. "Influenza-like symptom recognition using mobile sensing and graph neural networks." In ACM CHIL '21: ACM Conference on Health, Inference, and Learning. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3450439.3451880.

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Hong, Hanyu, Xiuhua Zhang, and Jiuyang Yu. "Fast detection and symptom analysis of cracks in highway asphalt pavement." In Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Mingyue Ding, Bir Bhanu, Friedrich M. Wahl, and Jonathan Roberts. SPIE, 2009. http://dx.doi.org/10.1117/12.832435.

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Adnan, Md Mohsinur Rahman, Fatima Tuz Zohora, Maliha Tasnim, Sutapa Debnath, and Sadia Anjum Tumpa. "Portable implementation of profuse perspiration indicator for use in disease symptom detection." In 2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR). IEEE, 2017. http://dx.doi.org/10.1109/icivpr.2017.7890874.

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