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

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

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

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

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

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

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

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

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

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

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

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

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

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