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Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data (Preprint)

Koustuv Saha, John Torous, Emre Kiciman, Munmun De Choudhury
2020 JMIR Mental Health  
One implication of this work concerns the potential of social media data as an effective means to support digital pharmacovigilance and digital therapeutics.  ...  We aim to understand the side effects of antidepressants from naturalistic expressions of individuals on social media.  ...  Acknowledgments KS and MDC were partly supported by National Institutes of Health grant #R01MH117172. Conflicts of Interest None declared.  ... 
doi:10.2196/26589 pmid:33739296 fatcat:3nricrr6tbak3okborrzwhq5wq

Crowdsourcing Health Labels: Inferring Body Weight from Profile Pictures [article]

Ingmar Weber, Yelena Mejova
2016 arXiv   pre-print
To use social media for health-related analysis, one key step is the detection of health-related labels for users.  ...  In this paper we investigate the feasibility of using profile pictures to infer if a user is overweight or not.  ...  Another generic approach to infer labels for a user in a social network is to incorporate knowledge and labels from their social connections.  ... 
arXiv:1602.07185v1 fatcat:sksyoj2y4jfytfcsjss3thubq4

Big Data and Social/Medical Sciences: State of the Art and Future Trends [article]

Adil E. Rajput, Samara M. Ahmed
2019 arXiv   pre-print
The explosion of data on the internet is a direct corollary of the social media platform.  ...  Furthermore, we provide guidelines for future work that will help in streamlining the Big Data use in social/medical sciences.  ...  Furthermore, the application of Big Data concepts to medical and social sciences lack a systematic approach.  ... 
arXiv:1902.00705v1 fatcat:odipl5p62jfmva6zggfvt7bfjy

Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions [article]

Azzam Mourad, Ali Srour, Haidar Harmanani, Cathia Jenainatiy, Mohamad Arafeh
2020 arXiv   pre-print
News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide.  ...  This paper presents a large-scale study based on data mined from Twitter.  ...  Abstract-News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide.  ... 
arXiv:2005.08820v1 fatcat:vzwmd5mwzjendeaq3vfol6yxw4

Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health

David C. Mohr, Michelle Nicole Burns, Stephen M. Schueller, Gregory Clarke, Michael Klinkman
2013 General Hospital Psychiatry  
This paper will provide a brief definition, explain why BITs research is high priority, present an overview of the research to date and outline the research challenges for the field.  ...  Web-based interventions have shown efficacy across a broad range of mental health outcomes. Social media such as online support groups have produced disappointing outcomes when used alone.  ...  Acknowledgments The authors have no conflicts of interest to disclose. Work on this paper was supported in part by NIMH grants R01-MH059708 and P20-MH090318.  ... 
doi:10.1016/j.genhosppsych.2013.03.008 pmid:23664503 pmcid:PMC3719158 fatcat:y6ifjghdmndvphcfemo735djvq

Musical mnemonics in health science: A first look

Matthew M. Cirigliano
2012 Medical Teacher  
Jacobsen for helping brainstorm an approach to this unusual topic. DECLARATION OF INTEREST The author has no declarations of interest to report.  ...  Eric Klotz for co-creating and co-performing two of the original songs used in this study. Dr. Kristin J.  ...  As researchers in social media are aware, extracting useful information from social media is not an easy task (Cambria, Hussain, Grassi & Havasi, 2011) and "…there is still a need for better tools and  ... 
doi:10.3109/0142159x.2012.733042 pmid:23110356 fatcat:2azs35utrnc3tpyd25qjtebzpm

Big Data Analytics and Pharmacovigilance—An Ethical and Legal Consideration

Jaswinder Singh, Rahat Kumar, Pratyush Sharma, MaheshInder Singha
2018 Current Trends in diagnosis & Treatment  
Big data" has become a more and more cited term in health care, for the potential use of the huge amount of data collected from digital medical records or administrative data (e.g., drug prescriptions,  ...  Utilization of big data in Pharmacovigilance will bring in the potential to complement traditional spontaneous reporting systems, by allowing an epidemiological approach to determine the incidence of adverse  ...  (e) Data from social media (Twitter, Facebook, blogs).  ... 
doi:10.5005/jp-journals-10055-0040 fatcat:dnufxhoitbcknhnlvea4ohatvu

Harnessing social media data for pharmacovigilance: a review of current state of the art, challenges and future directions

Dimitra Pappa, Lampros K. Stergioulas
2019 International Journal of Data Science and Analytics  
As the use of social media data for pharmacovigilance is still in its infancy, the present paper explores the state of the art in the application of social data to adverse drug reaction detection; provides  ...  In this context, health information posted online by patients represents a potentially valuable, yet currently left largely unexploited source of post-market safety data that could supplement data from  ...  and inferences from large data sets.  ... 
doi:10.1007/s41060-019-00175-3 fatcat:pbxbpcdihjfhrgm2nv3tomp3hm

Topic Modeling for Analyzing Patients' Perceptions and Concerns of Hearing Loss on Social Q&A Sites: Incorporating Patients' Perspective

Junghwa Bahng, Chang Heon Lee
2020 International Journal of Environmental Research and Public Health  
Our topic analysis of patients' questions on the topic of hearing loss allows achieving a thorough understanding of patients' perspectives, thereby leading to better development of the patient-centered  ...  " and "complications of disease".  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijerph17176209 pmid:32867035 fatcat:gjpu2tjnlven3krlxjeqstcl5y

Who Owns the Data? Open Data for Healthcare

Patty Kostkova, Helen Brewer, Simon de Lusignan, Edward Fottrell, Ben Goldacre, Graham Hart, Phil Koczan, Peter Knight, Corinne Marsolier, Rachel A. McKendry, Emma Ross, Angela Sasse (+5 others)
2016 Frontiers in Public Health  
Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual's characteristics  ...  Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming  ...  These technological advances created an unprecedented level of personal data sharing from wearable medical devices, social media, and personal fitness tracking, to loyalty cards recording our shopping  ... 
doi:10.3389/fpubh.2016.00007 pmid:26925395 pmcid:PMC4756607 fatcat:eyzitlycvbcxjpyb32bph2ph4y

Identifying information needs of patients with IgA Nephropathy, using an innovative social media stepped analytical approach

C. Vasilica, T. Oates, C. Clausner, P. Ormandy, J. Barratt, M.P.M. Graham-Brown
2021 Kidney International Reports  
The number of people with kidney disease using social media to search for medical information and peer support is increasing.  ...  These themes differed significantly from those identified from the traditional patient focus group, highlighting the value of this novel method for interrogating social media data to understand unmet patient  ...  between the potential needs of patients with IgAN as defined by a patient focus group compared with analysis of social media data.  ... 
doi:10.1016/j.ekir.2021.02.030 pmid:34013110 pmcid:PMC8116902 fatcat:saldn26xdnadpigr4bokolqww4

Causality-based Social Media Analysis for Normal Users Credibility Assessment in a Political Crisis

Ahmed Abouzeid, Ole.Christoffer Granmo, Christian Webersik, Morten Goodwin
2019 2019 25th Conference of Open Innovations Association (FRUCT)  
The polarity nature of political topics and the echo chamber effect by social media platforms allow for a deceptive and a dividing environment.  ...  The traditional approaches to tackling misinformation on social media usually lack a comprehensive problem definition due to its complication.  ...  The paper studies a potential novel approach to the problem by engaging a theoretical foundation from Bayesian analysis and causal inference [18] , [19] .  ... 
doi:10.23919/fruct48121.2019.8981500 dblp:conf/fruct/AbouzeidGWG19 fatcat:lxum2um2bfhc3lb4mo67upf2ci

Explainable-Machine-Learning to discover drivers and to predict mental illness during COVID-19 [article]

Indra Prakash Jha, Raghav Awasthi, Ajit Kumar, VIBHOR KUMAR, Tavpritesh Sethi
2020 medRxiv   pre-print
Integrating Bayesian networks with classical machine learning approaches lead to effective modeling of the level of mental health.  ...  Financial assistance from social security helps in reducing mental stress during COVID generated economic crises.  ...  An explainable probabilistic graphical modeling approach with bootstraps and exact inference allowed us to capture many of these effects in a robust manner.  ... 
doi:10.1101/2020.07.19.20157164 fatcat:jbkyp7g7knc6ted6anuvtjcy3u

Smart CDSS: integration of Social Media and Interaction Engine (SMIE) in healthcare for chronic disease patients

Iram Fatima, Sajal Halder, Muhammad Aamir Saleem, Rabia Batool, Muhammad Fahim, Young-Koo Lee, Sungyoung Lee
2013 Multimedia tools and applications  
All these outputs are supplied to Smart CDSS into vMR (virtual Medical Record) format through social media adapter.  ...  CDSS (Clinical Decision Support System) helps physician in effective utilization of patient's clinical information at the time of diagnosis and medication.  ...  Briefly explained, the process infers meaningful actions from the email data and then splits the string of actions into periodic sequences based on some frequency support to avoid any redundant information  ... 
doi:10.1007/s11042-013-1668-5 fatcat:ef4os33jojenvkin7vznvzmh3m

Exploring the Association Between the "Big Five" Personality Traits and Fatal Opioid Overdose: County-Level Empirical Analysis

Zhasmina Tacheva, Anton Ivanov
2021 JMIR Mental Health  
for using social media data to glean these psychological factors in a real-time, reliable, and scalable manner.  ...  We collected annual panel data from Twitter for 2891 counties in the United States between 2014-2016 and used a novel data mining technique to obtain average county-level "Big Five" psychological trait  ...  To ensure the reliability and consistency of our model, which seeks to explore the relationship between personality traits inferred from social media text data and fatal opiate overdose, we used an extensive  ... 
doi:10.2196/24939 pmid:33683210 pmcid:PMC7985797 fatcat:4yjhj7elfnghtjmftm3jryvoaq
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