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ChatGPT-4–Driven Liver Ultrasound Radiomics Analysis: Diagnostic Value and Drawbacks in a Comparative Study

ChatGPT-4–Driven Liver Ultrasound Radiomics Analysis: Diagnostic Value and Drawbacks in a Comparative Study

Seventy B-mode grayscale ultrasound images acquired from validated rat liver disease models [30-32] were used for analysis. The images were distributed across 3 categories of liver health: fibrosis (n=31), steatosis (fatty liver) (n=18), and normal (n=21). To maintain consistency and reliability in the analysis, the imaging parameters were standardized, including transducer frequency, gain settings, imaging depth, focus, and dynamic range.

Laith R Sultan, Shyam Sunder B Venkatakrishna, Sudha A Anupindi, Savvas Andronikou, Michael R Acord, Hansel J Otero, Kassa Darge, Chandra M Sehgal, John H Holmes

JMIR AI 2025;4:e68144

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study

(B) Digital measurements with the smart band Xiaomi Redmi Smart Band 8, starting on day one for controls, and after the first month of treatment for substance use disorder. (C) Evaluation of the emotional state during craving halfway through the digital monitoring period (third month), and at the end of it. (D) Data preprocessing is required for all 3 data sources. (E) Training in a machine learning predictive model in neural networks. (F) creation of a graphic user interface for clinical use.

Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

JMIR Res Protoc 2025;14:e71374

Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data

Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data

County B, on the east side of the state, is an urban county, with over 370,000 people. The jail had 404 beds and 8300 bookings in 2019. These jails vary in screening methods for suicide risk at jail booking, which reflects variability nationally. County A uses several scripted questions about current and past suicide ideation or attempts, and County B uses several scripted questions and a truncated version of the Columbia Suicide Severity Rating Scale [25]. The 2 jail populations vary demographically.

Erin B Comartin, Grant Victor, Athena Kheibari, Brian K Ahmedani, Bethany Hedden-Clayton, Richard N Jones, Ted R Miller, Jennifer E Johnson, Lauren M Weinstock, Sheryl Kubiak

JMIR Res Protoc 2025;14:e68517