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Natural Language Processing for Identification of Hospitalized People Who Use Drugs: Cohort Study

Natural Language Processing for Identification of Hospitalized People Who Use Drugs: Cohort Study

The presence of any of the following criteria (ie, abbreviated with the letters B, D, M, and N) were used to qualify the hospitalizations for inclusion in the PWUD cohort: B (Biomarkers): In line with a previous study, positive urine toxicology for drugs or medications for SUD (eg, cocaine, amphetamine, methadone, suboxone, fentanyl, opiate, oxycodone), positive HCV antibody with positive or quantifiable HCV viral load [29] D (Diagnostic codes): Presence of ICD-9 and or ICD-10 code for overdose, substance use

Taisuke Sato, Emily D Grussing, Ruchi Patel, Jessica Ridgway, Joji Suzuki, Benjamin Sweigart, Robert Miller, Alysse G Wurcel

JMIR AI 2025;4:e63147

Performance of a Retinal Imaging Camera With On-Device Intelligence for Primary Care: Retrospective Study

Performance of a Retinal Imaging Camera With On-Device Intelligence for Primary Care: Retrospective Study

(D) Image quality control feature “not pass” and ungradable, due to eyelash artifacts. There was agreement among 100% (15/15) of the participating users in the simulated clinic environment that they were able to have both eyes screened easily.

Matthew Silvestrini, Clarissa Lui, Anil Patwardhan, Ying Chen, Tayyeba Ali, Elie Glik, Honglei Wu, Brian Levinstein, Adrianna Wenz, Nathan Shemonski, Lin Yang, Ian Atkinson, Sam Kavusi

JMIR Form Res 2025;9:e70331