Results 171 to 180 of about 43,074 (218)

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Evaluating the Quality of Artificial Intelligence-Generated Information on Cleft Lip and Palate: A Comparative Cross-Sectional Study. [PDF]

Healthcare (Basel)
Bilder A, Almos M, Hija A, Krasovsky A, Zeineh N, Capucha T, Emodi O.   +6 more
europepmc   +1 more source

Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly comprise research validity. Drawing from our experience using Qualtrics with open recruitment, existing literature, and emerging studies in eating disorders (ED), we outline the risk and provide simple ...
Jamie‐Lee Pennesi, Mia L. Pellizzer, Tracey D. Wade   +2 more
wiley   +1 more source

Expert evaluation of GPT-4o and Gemini responses to patient questions on carotid endarterectomy. [PDF]

Rev Assoc Med Bras (1992)
Rahman ÖF, Özbakkaloğlu A, Arslangilay M, Daylan A, Keleş E, Bozkurt ÖT, Bozok A.   +6 more
europepmc   +1 more source

Daily Body (Dis‐)Satisfaction and Dietary Restriction in Women Across the Eating Disorder Spectrum

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective Body dissatisfaction is a key risk factor in eating disorder development: It is theorized to promote dietary restriction, thereby contributing to symptom onset. Evidence for this pathway primarily comes from cross‐sectional or multi‐wave questionnaire studies in bulimia nervosa (BN) and anorexia nervosa (AN).
Michaela R. Buehler, Ann‐Kathrin Arend, Julia Reichenberger, Jens Blechert   +3 more
wiley   +1 more source

Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow. [PDF]

STAR Protoc
Hamed AA, Rocha LM.
europepmc   +1 more source

A Comparative Evaluation of Three Large Language Models for Parent‐Centered Questions About Anorexia Nervosa

International Journal of Eating Disorders, EarlyView.
ABSTRACT Background Large language models (LLMs) are increasingly used to obtain health information, including guidance on child and adolescent mental health. In anorexia nervosa (AN), where early recognition and timely intervention are critical, the accuracy of AI‐generated information available to parents may have important clinical implications ...
Celal Yeşilkaya, Hande Kırışman Keleş, Esra Rabia Taşpolat, Caner Mutlu, Serkan Turan   +4 more
wiley   +1 more source

Real-Time Evaluation of a Large Language Model for Clinical Practice Guideline Development. [PDF]

Crit Care Explor
Erstad BL.
europepmc   +1 more source

Ecological Momentary Interventions in the Management of Eating Disorders and Obesity: A Systematic Review

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective This systematic review evaluated the feasibility, efficacy, adherence, and methodological quality of ecological momentary intervention (EMI)–based treatments for individuals with diagnosed eating disorders (EDs) and/or obesity. Method Eight electronic databases were systematically searched from inception to January 2026.
Wenlu Mao, Ricarda Schmidt, Emily K. Presseller, Adrienne Juarascio, Anja Hilbert   +4 more
wiley   +1 more source

MT-ConBiFormer-GPT: multi-target molecular generation for low-data drug discovery via a contrastive BiFormer-GPT architecture and curriculum learning with cross-domain generalization. [PDF]

Brief Bioinform
Norouzi R, Abbasi K, Razzaghi P, Gharaghani S.   +3 more
europepmc   +1 more source