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Construct validity of six sentiment analysis methods in the text of encounter notes of patients with critical illness

Gary E. Weissman, Lyle H. Ungar, Michael O. Harhay, Katherine R. Courtright, Scott D. Halpern
2019 Journal of Biomedical Informatics  
Sentiment analysis may offer insights into patient outcomes through the subjective expressions made by clinicians in the text of encounter notes.  ...  We analyzed the predictive, concurrent, convergent, and content validity of six sentiment methods in a sample of 793,725 multidisciplinary clinical notes among 41,283 hospitalizations associated with an  ...  Acknowledgments Funding GEW received support from the National Institutes of Health (T32-HL098054, K23-HL141639). MOH received support from the National Institutes of Health (K99-HL141678).  ... 
doi:10.1016/j.jbi.2018.12.001 pmid:30557683 pmcid:PMC6342660 fatcat:rmp4ov67fbfczezch2sbtrojdy

Applications of Aspect-based Sentiment Analysis on Psychiatric Clinical Notes to Study Suicide in Youth

Amy George, David Johnson, Giuseppe Carenini, Ali Eslami, Raymond Ng, Elodie Portales-Casamar
2021 AMIA Annual Symposium Proceedings  
Understanding and identifying the risk factors associated with suicide in youth experiencing mental health concerns is paramount to early intervention. 45% of patients are admitted annually for suicidality  ...  Our objective was to explore whether machine-learning-based sentiment analysis could be informative in such a prediction task.  ...  Acknowledgements We acknowledge financial support for this project from 1) the BC SUPPORT Unit Data Science and Health Informatics Methods Cluster (Award Number: DaSHI-002), which is part of British Columbia's  ... 
pmid:34457137 pmcid:PMC8378644 fatcat:xvffg2sxizef3jpvvhmnmhk47q

A review and meta-analysis of machine intelligence approaches for mental health issues and depression detection

Ravita Chahar, Ashutosh Kumar Dubey, Sushil Kumar Narang
2021 International Journal of Advanced Technology and Engineering Exploration  
An increase of 11% from the previous year was noted in the US alone due to the COVID-19 pandemic [6, 7] . The best way to detect depression is to analyze the behavior of the person.  ...  As per the WHO report in 2017, over 300 million people (equivalent to 4.4% of the world's population) worldwide are estimated to suffer from depression [5] .  ...  Based on the analysis of the studies conducted in 2015-2021, the following advantages and limitations were encountered in the approaches used for the detection of mental illness and depression disorders  ... 
doi:10.19101/ijatee.2021.874198 fatcat:bhrusmlbdrdvfkcnob4ueowaam

VisOHC: Designing Visual Analytics for Online Health Communities

Bum Chul Kwon, Sung-Hee Kim, Sukwon Lee, Jaegul Choo, Jina Huh, Ji Soo Yi
2016 IEEE Transactions on Visualization and Computer Graphics  
Through online health communities (OHCs), patients and caregivers exchange their illness experiences and strategies for overcoming the illness, and provide emotional support.  ...  The main challenge of OHC administrators' tasks lies in understanding the diverse dimensions of conversation threads that lead to productive discussions in their communities.  ...  Research reported in this paper was in part supported by National Library of Medicine of the National Institutes of Health under award number K01LM011980.  ... 
doi:10.1109/tvcg.2015.2467555 pmid:26529688 pmcid:PMC4638132 fatcat:eiwhatmsvfdetnx2qz7knv5ckq

Digital methods to enhance the usefulness of patient experience data in services for long-term conditions: the DEPEND mixed-methods study

Caroline Sanders, Papreen Nahar, Nicola Small, Damian Hodgson, Bie Nio Ong, Azad Dehghan, Charlotte A Sharp, William G Dixon, Shôn Lewis, Evangelos Kontopantelis, Gavin Daker-White, Peter Bower (+14 others)
2020 Health Services and Delivery Research  
Design The DEPEND study is a mixed-methods study with four parts: qualitative research to explore the perspectives of patients, carers and staff; use of computer science text-analytics methods to analyse  ...  Collecting NHS patient experience data is critical to ensure the delivery of high-quality services.  ...  Andrew Shepherd ( (NIHR Clinical Lecturer) contributed to the comparison of the qualitative analysis with text mining, analysis of the primary qualitative data and  ... 
doi:10.3310/hsdr08280 fatcat:xfsqu2euvjhqliibu5z4linpre

"My bitterness is deeper than the ocean": understanding internalized stigma from the perspectives of persons with schizophrenia and their family caregivers

Yin-Ling Irene Wong, Dexia Kong, Lufei Tu, Rosemary Frasso
2018 International Journal of Mental Health Systems  
Scores from the two scales and number of text fragments were compared to identify consistency of responses using the two methods.  ...  Caregivers expressed high level of emotional distress because of mental illness in the family. Family dyads varied in the extent that internalized stigma were experienced by patients and caregivers.  ...  Acknowledgements The study is indebted to persons with schizophrenia and their family members who participated in this study and shared their stories with us.  ... 
doi:10.1186/s13033-018-0192-4 pmid:29636792 pmcid:PMC5883360 fatcat:tsg5jjzvh5f2jebnzghp3zduty

Measuring Mental Illness Stigma

B. G. Link, L. H. Yang, J. C. Phelan, P. Y. Collins
2004 Schizophrenia Bulletin  
Critical to such an understanding is our capacity to observe and measure the essential components of stigma processes.  ...  The effectiveness of efforts designed to address mental illness stigma will rest on our ability to understand stigma processes, the factors that produce and sustain such processes, and the mechanisms that  ...  The analysis of interviews, field notes, and informal interviews reveals that most patients opt to reject the psychiatric explanation of their problems and the negative social implications of psychiatric  ... 
doi:10.1093/oxfordjournals.schbul.a007098 pmid:15631243 fatcat:snliyu275rhzvbsyoxor5p77ym

Negation recognition in medical narrative reports

Lior Rokach, Roni Romano, Oded Maimon
2008 Information retrieval (Boston)  
When searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the documents retrieved will be irrelevant.  ...  We present a new pattern learning method for automatic identification of negative context in clinical narratives reports.  ...  Acknowledgements (Tel-Aviv Sourasky Medical Center, Israel) for providing the data that have been used in the experimental study and for helping doing the initial prior studies which lead eventually to  ... 
doi:10.1007/s10791-008-9061-0 fatcat:at5rdoqxuvhm5gaz57etmcxbzq

Sehaa: A Big Data Analytics Tool for Healthcare Symptoms and Diseases Detection Using Twitter, Apache Spark, and Machine Learning

Shoayee Alotaibi, Rashid Mehmood, Iyad Katib, Omer Rana, Aiiad Albeshri
2020 Applied Sciences  
Sehaa uses Naive Bayes, Logistic Regression, and multiple feature extraction methods to detect various diseases in the KSA.  ...  Riyadh and Jeddah need to do more in creating awareness about the top diseases. Taif is the healthiest city in the KSA in terms of the detected diseases and awareness activities.  ...  Acknowledgments: The work carried out in this paper was supported by the HPC center at King Abdulaziz University. Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/app10041398 fatcat:3kqquusgevf2vmi6gmftyfzkp4

Structured measurement of personality and motivation: A review of contributions of Raymond B. Cattell

Saul B. Sells
1959 Journal of Clinical Psychology  
Factor analysis is employed in this research as an heuristic method, to discover structure, not to confirm it, although some of the experimental designs involve matching factors with criterion data which  ...  The processes involved in this approach are not automatic, however, since they call for sophistication and effort both in test construction and in factor analysis, the latter primarily in the interpretive  ... 
doi:10.1002/1097-4679(195901)15:1<3::aid-jclp2270150102>;2-9 pmid:13611053 fatcat:frrxv4yj3rc5pe45dmmpm4mwgq

Text classification for assisting moderators in online health communities

Jina Huh, Meliha Yetisgen-Yildiz, Wanda Pratt
2013 Journal of Biomedical Informatics  
Using sentiment analysis features, feature selection methods, and balanced training data increased the AUC value up to 0.75 and the F1-score up to 0.54 compared to the baseline of using word unigrams with  ...  Our work explores low-cost text classification methods to this new domain of determining whether a thread in an online health forum needs moderators' help.  ...  We also thank the iMed group, David McDonald, Andrea Hartzler, Mark S. Ackerman, and Moon-Yul Huh for support.  ... 
doi:10.1016/j.jbi.2013.08.011 pmid:24025513 pmcid:PMC3874858 fatcat:jk4vq46rnrfdxjsroadpqahxea

Beyond Social Media Analytics: Understanding Human Behaviour and Deep Emotion using Self Structuring Incremental Machine Learning [article]

Tharindu Bandaragoda
2020 arXiv   pre-print
Identified events were validated against contemporary events reported in news.  ...  patients.  ...  Note that ANALYSIS OF THE QUALITY OF LIFE OF PROSTATE CANCER PATIENTS151 the time factor is not considered in this study, thus, side-effects and emotions captured in the patient timeline are aggregated  ... 
arXiv:2009.09078v1 fatcat:izo3eyjc4vdo3jnttt7omvsv5q

Artificial Intelligence in Action: Addressing the COVID-19 Pandemic with Natural Language Processing

Qingyu Chen, Robert Leaman, Alexis Allot, Ling Luo, Chih-Hsuan Wei, Shankai Yan, Zhiyong Lu
2021 Annual Review of Biomedical Data Science  
We also describe work that directly addresses aspects of the pandemic through four additional tasks: topic modeling, sentiment and emotion analysis, caseload forecasting, and misinformation detection.  ...  The COVID-19 (coronavirus disease 2019) pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow  ...  ACKNOWLEDGMENTS This research is supported by the NIH Intramural Research Program, National Library of Medicine.  ... 
doi:10.1146/annurev-biodatasci-021821-061045 pmid:34465169 fatcat:gxtcwu5ih5gx3la6ea4674pnmu

What Goes Around Comes Around: Learning Sentiments in Online Medical Forums

Victoria Bobicev, Marina Sokolova, Michael Oakes
2015 Cognitive Computation  
As well as considering the predominant sentiments expressed in individual posts, we analyze sequences of sentiments in online discussions. Individual posts are classified into one of five categories.  ...  The annotated posts were used to analyse sentiments in consecutive posts.  ...  Figure 2: Correspondence analysis of sentiments Note that there are no significant words in the fourth quadrant.  ... 
doi:10.1007/s12559-015-9327-y fatcat:3xclttmi2nf5fbmtjpnxqvw2eq

Commenting on chiropractic: A YouTube analysis

Alessandro R. Marcon, Timothy Caulfield, Udo Schumacher
2017 Cogent Medicine  
) and opened in LibreOffice for analysis:  ...  If debates were present, the goal was then to use iterative coding methods to map out how debates were unfolding by describing the general characteristics of the discussions as well as the arguments used  ...  On a positive note regarding the constructive nature of many of the debates, "real questions" (information being requested by commenters) were found in 100% of the discussions, and technical All other  ... 
doi:10.1080/2331205x.2016.1277450 fatcat:sncdn5hhpvaz3mtlpdvbfyrx5i
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