Results 221 to 230 of about 176,171 (277)

Assessing Large Language Models for Early Article Identification in Otolaryngology—Head and Neck Surgery Systematic Reviews

Health Care Science, EarlyView.
The search criteria for three systematic reviews were replicated using ChatGPTv3.5 and Bard. Outputs included author, title, publication year, and journal and were cross‐referenced with medical databases and compared to the original reviews. Large language models failed to replicate peer‐reviewed methodologies.
Ajibola B. Bakare, Young Lee, Jhuree Hong, Claus‐Peter Richter, Jonathan P. Kuriakose   +4 more
wiley   +1 more source

Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study. [PDF]

JMIR AI
Miftaroski A, Zowalla R, Wiesner M, Pobiruchin M.   +3 more
europepmc   +1 more source

The Digital Diagnostic Odyssey: Artificial Intelligence and Social Media Crowdsourcing Amid Pediatric Neurology Access Gaps

Annals of the Child Neurology Society, EarlyView.
Audrey M. Smith, Rachel Vassar
wiley   +1 more source

A Survey on Medical Competence Evaluation Benchmarks for Large Language Models

Health Care Science, EarlyView.
Our study presents a comprehensive review of the established methodologies and benchmarks for evaluating the medical competence of LLMs, encompassing a thorough analysis of current assessment practices across medical knowledge, clinical practice competence, and ethical–safety considerations.
Qiting Wang, Huiru Zou, Haobin Zhang, Yongshun Huang, Junzhang Tian, Weibin Cheng   +5 more
wiley   +1 more source

Preferences of Chinese Dermatologists for Large Language Model Responses in Clinical Psoriasis Scenarios: A Nationwide Cross‐Sectional Survey in China

Health Care Science, EarlyView.
In a nationwide survey of 1247 Chinese dermatologists, ChatGPT‐4o was the most preferred large language model (LLM) for psoriasis‐related clinical tasks. Accuracy emerged as the top evaluation criterion for LLM‐generated responses. All icons were made by Freepik and Maan Icons from https://www.flaticon.com/ ABSTRACT Background Large language models ...
Jungang Yang, Jingkai Xu, Xuejiao Song, Chengxu Li, Lili Chen, Lingbo Bi, Tingting Jiang, Xianbo Zuo, Yong Cui   +8 more
wiley   +1 more source

Leveraging generative AI to enhance Synthea model development. [PDF]

JAMIA Open
Kramer MA, Mathur A, Adams CE, Walonoski JA.   +3 more
europepmc   +1 more source

Prevalence and risk factors for postpartum depression and stress among mothers of preterm and low birthweight infants admitted to a neonatal intensive care unit in Accra, Ghana

International Journal of Gynecology &Obstetrics, Volume 169, Issue 1, Page 131-137, April 2025.
Abstract To determine the prevalence of postpartum depression (PPD) and postpartum stress (PPS) and identify associated risk factors among mothers of preterm and low birth weight (LBW) infants. We conducted a secondary analysis of data collected from 255 mothers with preterm and LBW infants admitted to the neonatal intensive care unit (NICU) at Korle ...
John Pellegrino, Paddington T. Mundagowa, Kwame Sarfo Sakyi, Prince Gyebi Owusu, Babbel Agbinko‐Djobalar, Leila M. Larson, Mufaro Kanyangarara   +6 more
wiley   +1 more source

Automated information extraction from plant specimen labels using OCR and large language models. [PDF]

Biodivers Data J
Wen J.
europepmc   +1 more source

Artificial intelligence in obstetrics and gynecology: Evaluating ChatGPT and Google Gemini in answering patient questions

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Introduction To evaluate the accuracy and completeness of responses across common obstetrical and gynecologic topics generated by the large language models (LLMs) ChatGPT and Google Gemini, which have become increasingly popular for patients seeking medical information before physician consultations.
Madeline West, Amir Alsaidi, Rohail Siddiqi, Fatima Sayyed, Rachael Counts, Lauren Quinto, Nicholas Stansbury   +6 more
wiley   +1 more source