Results 231 to 240 of about 176,171 (277)

Evaluating Medical Text Summaries Using Automatic Evaluation Metrics and LLM-as-a-Judge Approach: A Pilot Study. [PDF]

Diagnostics (Basel)
Vasilev Y, Raznitsyna I, Pamova A, Burtsev T, Bobrovskaya T, Kosov P, Vladzymyrskyy A, Omelyanskaya O, Arzamasov K.   +8 more
europepmc   +1 more source

CellOntologyMapper: Consensus mapping of cell type annotation

iMetaOmics, EarlyView.
CellOntologyMapper automates the standardization of cell type annotations in single‐cell RNA‐seq by mapping user‐defined names to the Cell Ontology (CL) and Cell Taxonomy (CT). The framework constructs a comprehensive embedding database of 19,381 curated cell types using sentence transformers, large language models, and synonym expansion.
Zehua Zeng, Xuehai Wang, Hongwu Du, Cencan Xing   +3 more
wiley   +1 more source

A Pilot Study on the Accuracy of Large Language Models (ChatGPT, Google Bard, and Microsoft Copilot) for Selecting the Correct Modality for Musculoskeletal Clinical Cases According to the ACR's Appropriateness Criteria

iRADIOLOGY, EarlyView.
In this paper we demonstrate that AI models can determine the most appropriate imagining modality for a given musculoskeletal clinical scenario in up to 89% of cases, with some models outperforming others. ABSTRACT Background Large language models (LLMs) are becoming more commonly used in many aspects of radiology.
Thomas Saliba, Patrick Omoumi, Grammatina Boitsios   +2 more
wiley   +1 more source

More polished, not necessarily more learned: LLMs and perceived text quality in higher education. [PDF]

Front Artif Intell
Tärning B, Tjøstheim TA, Wallin A.
europepmc   +1 more source

Enhancing Dental Students' History‐taking Skills with a Generative Artificial Intelligence Chatbot

Journal of Dental Education, EarlyView.
ABSTRACT Purpose Accurate history‐taking is crucial for diagnosis and treatment planning in dentistry yet there is insufficient time in pre‐clinical years to practice this essential skill. This study evaluated dental student motivations and enjoyment using a generative artificial intelligence (AI) chatbot to practice these skills.
Aidan Or, Smitha Sukumar, Andrew Ma, Derick Ang, Max Liu, Helen E. Ritchie, Babak Sarrafpour   +6 more
wiley   +1 more source

LLM4FB: A One-Sided CSI Feedback and Prediction Framework for Lightweight UEs via Large Language Models. [PDF]

Sensors (Basel)
Xie X, Ning X, Liu Y, Wang H, Jin J, Yang H.   +5 more
europepmc   +1 more source

Leveraging AI Large Language Models for Writing Clinical Trial Proposals in Dermatology: Instrument Validation Study. [PDF]

JMIR Dermatol
Hauptman M, Copley D, Young K, Do T, Durgin JS, Yang A, Chang J, Billi A, Nakamura M, Tejasvi T.   +9 more
europepmc   +1 more source

The Ethical Boundaries of Chairside Generative Artificial Intelligence in Dental Education

Journal of Dental Education, EarlyView.
ABSTRACT In dental school clinics, students are increasingly using Generative Artificial Intelligence (GenAI) tools like ChatGPT during patient care. This chairside, or point of care, use raises ethical concerns, particularly around supervision, patient safety, and training quality. This paper argues that GenAI can be ethically used in dental education
Sonal Anand, Ram Vaderhobli
wiley   +1 more source

Invisible Text Injection and Peer Review by AI Models.

JAMA Netw Open
Choi B, Jun TJ, Sung JW, Park IW, Lee JM, Cho SI, Park HJ, Lee RW, Suh J.   +8 more
europepmc   +1 more source

Comment on "A positive spin: large language models can help directors evaluate programs through their patients' own words". [PDF]

Pain Rep
Daungsupawong H, Wiwanitkit V.
europepmc   +1 more source