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Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation

Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation

All the extracted data were de-identified. The performance of Chat GPT was first evaluated using a seizure semiology database compiled from publicly available studies in published peer-reviewed journals. Furthermore, to mitigate the risk of testing the performance with data that may have been used during Chat GPT’s training, another private data cohort was constructed based on electronic health records (EHRs) from Far Eastern Memorial Hospital (FEMH) in Taiwan for external validation.

Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu

J Med Internet Res 2025;27:e69173

Effect of Early Treatment of Spasticity After Stroke on Motor Recovery: Protocol for the Baclotox Multicenter, Double-Blind, Double-Dummy Randomized Controlled Trial

Effect of Early Treatment of Spasticity After Stroke on Motor Recovery: Protocol for the Baclotox Multicenter, Double-Blind, Double-Dummy Randomized Controlled Trial

Despite its widespread use and endorsement by the French National Health Authority, Haute Autorité de Santé, as a first-line treatment, studies in animal models have raised concerns about the impact of GABAergic drugs on motor recovery. Research indicates that GABAergic agents, such as diazepam, can impair motor recovery and brain plasticity postinjury [10,11].

Emmeline Montane, Nabila Brihmat, Camille Cormier, Claire Thalamas, Vanessa Rousseau, Gerard Tap, Xavier De Boissezon, Evelyne Castel-Lacanal, Baclotox Group, Philippe Marque

JMIR Res Protoc 2025;14:e62951

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Reference 14: Machine learning in de pijnrevalidatie en de revalidatiearts als primaire belanghebbende (https://www.revalidatie.nl/ntr/machine-learning-in-de-pijnrevalidatie-en-de-revalidatiearts-als-primaire-belanghebbende

Fredrick Zmudzki, Rob J E M Smeets, Jan S Groenewegen, Erik van der Graaff

JMIR Rehabil Assist Technol 2025;12:e65890

Evolution of Learning Styles in Surgery Comparing Residents and Teachers: Cross-Sectional Study

Evolution of Learning Styles in Surgery Comparing Residents and Teachers: Cross-Sectional Study

This cross-sectional study was conducted in 2022 at the Hospital de Base de São José do Rio Preto, a teaching hospital affiliated with Faculdade de Medicina de São José do Rio Preto (a public university in São Paulo, Brazil). The study population consisted of general surgery residents in any year of training and hospital professors. All participants were over 18 years old and signed the free and informed consent form. Data collection involved two instruments: a sociodemographic survey and David Kolb’s LSI.

Gabriela Gouvea Silva, Carlos Dario da Silva Costa, Bruno Cardoso Gonçalves, Luiz Vianney Saldanha Cidrão Nunes, Emerson Roberto dos Santos, Natalia Almeida de Arnaldo Rodriguez Castro, Alba Regina de Abreu Lima, Vânia Maria Sabadoto Brienze, Antônio Hélio Oliani, Júlio César André

JMIR Med Educ 2025;11:e64767

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Analyses were done with R (v4.2.2, R Foundation for Statistical Computing). This study was approved by the University of Otago Human Ethics Committee (reference: HD22/064). Participants were users of a commercially available app who consented to their anonymized data being used for research purposes through the app’s privacy policy. All data were deidentified before analysis. No compensation was provided for participation.

Michelle R Jospe, Martin Kendall, Susan M Schembre, Melyssa Roy

JMIR Form Res 2025;9:e65368

Investigating Social Network Peer Effects on HIV Care Engagement Using a Fuzzy-Like Matching Approach: Cross-Sectional Secondary Analysis of the N2 Cohort Study

Investigating Social Network Peer Effects on HIV Care Engagement Using a Fuzzy-Like Matching Approach: Cross-Sectional Secondary Analysis of the N2 Cohort Study

We used R (version 12.1.402; R Foundation for Statistical Computing [34]) and Microsoft Excel (Microsoft Corp) for data analysis and matching. The boundaries of the final complete sociocentric-like fuzzy network were only those participants enrolled in the N2 cohort study and did not include those individuals that participants may have named as being in their social networks.

Cho-Hee Shrader, Dustin T Duncan, Redd Driver, Juan G Arroyo-Flores, Makella S Coudray, Raymond Moody, Yen-Tyng Chen, Britt Skaathun, Lindsay Young, Natascha del Vecchio, Kayo Fujimoto, Justin R Knox, Mariano Kanamori, John A Schneider

JMIR Public Health Surveill 2025;11:e64497