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AI-Powered Drug Classification and Indication Mapping for Pharmacoepidemiologic Studies: Prompt Development and Validation

AI-Powered Drug Classification and Indication Mapping for Pharmacoepidemiologic Studies: Prompt Development and Validation

Using the example of lisinopril and hydrochlorothiazide, the first level ATC code is “C” for cardiovascular, the organ or system acted upon, the second-level ATC code is “C09” for agents acting on the renin–angiotensin system, and the fifth-level ATC code is “C09 BA03”: lisinopril and diuretics [12,13]. While there is the basic principle of 1 ATC code for each drug [12], here the fifth-level ATC code is still ambiguous due to the presence of an unspecified diuretic.

Benjamin Ogorek, Thomas Rhoads, Eric Finkelman, Isaac R Rodriguez-Chavez

JMIR AI 2025;4:e65481

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Feasibility and Usability of a Web-Based Peer Support Network for Care Partners of People With Serious Illness (ConnectShareCare): Observational Study

Feasibility and Usability of a Web-Based Peer Support Network for Care Partners of People With Serious Illness (ConnectShareCare): Observational Study

We used statistical process control c Charts [18] to identify changes in enrollment and engagement over time. We used descriptive statistics to summarize categorical information from survey responses. We conducted descriptive statistics with SPSS (version 28; IBM Corp). Subgroup analyses were not conducted due to the small sample size. Missing data were excluded on an analysis-by-analysis basis.

Aricca D Van Citters, Megan M Holthoff, Colleen Young, Sarah M Eck, Amelia M Cullinan, Stephanie Carney, Elizabeth A O'Donnell, Joel R King, Malavika Govindan, David Gustafson, Stephanie C Tomlin, Anne B Holmes, Ann D Bradley, Brant J Oliver, Matthew M Wilson, Eugene C Nelson, Amber E Barnato, Kathryn B Kirkland

JMIR Form Res 2025;9:e70206

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Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study

Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study

Note that this approach is inherently personalized, as the parameters a, b, c, d, and noise variance are estimated separately for each participant rather than for the overall population. All participants have the same linear-Gaussian model structure, but the parameters are estimated individually to create a personalized model that best explains their observed behavior.

Eric Pulick, John Curtin, Yonatan Mintz

JMIR Form Res 2025;9:e73265

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Article has an altmetric score of 1