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Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives: Text Mining Study

One recent research paper commented that “...there is no systematic way to extract information from these [police] narratives other than by manual review” [11].Still, automated methods for large-scale processing of free text known as text mining have been used

George Karystianis, Armita Adily, Peter Schofield, Lee Knight, Clara Galdon, David Greenberg, Louisa Jorm, Goran Nenadic, Tony Butler

J Med Internet Res 2018;20(9):e11548

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Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study

Indeed, one recent research paper commented that “…there is no systematic way to extract information from these [police] narratives other than by manual review” [25].Automated methods for large-scale processing of free text known as text mining have been used

George Karystianis, Annabeth Simpson, Armita Adily, Peter Schofield, David Greenberg, Handan Wand, Goran Nenadic, Tony Butler

J Med Internet Res 2020;22(12):e23725

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Detecting and Filtering Immune-Related Adverse Events Signal Based on Text Mining and Observational Health Data Sciences and Informatics Common Data Model: Framework Development Study

[28] and built an irAE-related literature text-mining dataset.

Yue Yu, Kathryn Ruddy, Aaron Mansfield, Nansu Zong, Andrew Wen, Shintaro Tsuji, Ming Huang, Hongfang Liu, Nilay Shah, Guoqian Jiang

JMIR Med Inform 2020;8(6):e17353

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Text Mining and Natural Language Processing Approaches for Automatic Categorization of Lay Requests to Web-Based Expert Forums

Typical text-mining tasks include, besides others, text categorization, concept/entity extraction, sentiment analysis, and document summarization.

Wolfgang Himmel, Ulrich Reincke, Hans Wilhelm Michelmann

J Med Internet Res 2009;11(3):e25

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Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach

published on the applications of text mining to Web data.

Adeline Abbe, Bruno Falissard

JMIR Ment Health 2017;4(4):e48

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Text Mining of United States Obesity-Related Public Policies: Systematic Document Search

mining, in order to identify which areas of knowledge have guided the development of these policies.

Caroline Spanhol-Finocchio, Mariana de Freitas Dewes, Giana de Vargas Mores, Homero Dewes

JMIR Public Health Surveill 2020;6(3):e13235

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Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic

One solution to the lack of structured information is natural language processing (NLP).Biomedical text mining, or the use of textual data, in electronic health records (EHRs) has often been proposed as a method for converting unstructured data to the structured

Antoine Neuraz, Ivan Lerner, William Digan, Nicolas Paris, Rosy Tsopra, Alice Rogier, David Baudoin, Kevin Bretonnel Cohen, Anita Burgun, Nicolas Garcelon, Bastien Rance, AP-HP/Universities/INSERM COVID-19 Research Collaboration; AP-HP COVID CDR Initiative

J Med Internet Res 2020;22(8):e20773

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E-Cigarette Social Media Messages: A Text Mining Analysis of Marketing and Consumer Conversations on Twitter

study used a text-mining approach to uncover key patterns and relationships within unstructured data to understand and evaluate information important to the audience.

Allison J Lazard, Adam J Saffer, Gary B Wilcox, Arnold DongWoo Chung, Michael S Mackert, Jay M Bernhardt

JMIR Public Health Surveill 2016;2(2):e171

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What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques

Moreover, social media mining has also been employed to understand the public’s impression of products that have health implications [7].

Annie T Chen, Shu-Hong Zhu, Mike Conway

J Med Internet Res 2015;17(9):e220

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Identifying Clinical Terms in Medical Text Using Ontology-Guided Machine Learning

IntroductionBackgroundAutomatic recognition of medical concepts in unstructured text is a key component of biomedical information retrieval systems.

Aryan Arbabi, David R Adams, Sanja Fidler, Michael Brudno

JMIR Med Inform 2019;7(2):e12596

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