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Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

To perform the eligibility assessment, we used the following inclusion criteria: empirical studies that (1) developed or tested AI methods, (2) developed or tested CDSS or CDSS components, and (3) focused on pregnancy care.

Xinnian Lin, Chen Liang, Jihong Liu, Tianchu Lyu, Nadia Ghumman, Berry Campbell

J Med Internet Res 2024;26:e54737

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Article has an altmetric score of 2

Patient Recruitment Into a Multicenter Clinical Cohort Linking Electronic Health Records From 5 Health Systems: Cross-sectional Analysis

Patient Recruitment Into a Multicenter Clinical Cohort Linking Electronic Health Records From 5 Health Systems: Cross-sectional Analysis

We identified participants using EHR-based eligibility criteria (ie, the “computable phenotype”). Eligible patients were aged ≥18 years and had a minimum of 2 weight measurements and 1 height measurement recorded between January 1, 2011, and May 31, 2015. Patients in all BMI categories were eligible. Participants were excluded if they were deceased or non–English proficient, as assessed at the time of consent, because the consent form and survey were only available in the English language.

Wendy L Bennett, Carolyn T Bramante, Scott D Rothenberger, Jennifer L Kraschnewski, Sharon J Herring, Michelle R Lent, Jeanne M Clark, Molly B Conroy, Harold Lehmann, Nickie Cappella, Megan Gauvey-Kern, Jody McCullough, Kathleen M McTigue

J Med Internet Res 2021;23(5):e24003

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Article has an altmetric score of 3