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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

Multicriteria Optimization of Language Models for Heart Failure With Preserved Ejection Fraction Symptom Detection in Spanish Electronic Health Records: Comparative Modeling Study

Multicriteria Optimization of Language Models for Heart Failure With Preserved Ejection Fraction Symptom Detection in Spanish Electronic Health Records: Comparative Modeling Study

Excerpt from the annotation guide with some of the expressions used to label the dataset (English translation is included to facilitate reading). a ICC: insuficiencia cardiaca congestiva. b FEVI: fracción de eyección del ventrículo izquierdo. c IC: insuficiencia cardiaca. d FE: fracción de eyección. e CF: clase funcional. f EAP: edema agudo pulmonar. g NYHA: New York Heart Association. h CHF: congestive heart failure. i LVEF: left ventricular ejection fraction. j HF: heart failure. k EF: ejection fraction. l APE: acute

Jacinto Mata, Victoria Pachón, Ana Manovel, Manuel J Maña, Manuel de la Villa

J Med Internet Res 2025;27:e76433