Results 181 to 190 of about 8,163 (222)

IMPACT: an interactive multi-disease prevention and counterfactual treatment system using explainable AI and a multimodal LLM. [PDF]

PeerJ Comput Sci
Mohanty PK, Anand John Francis S, Barik RK, Reddy KHK, Sinha Roy D, Saikia MJ.   +5 more
europepmc   +1 more source

The Italian Portrait of Laboratory Information Systems in Pathology: The Ones We Have and the Ones We Would Like. [PDF]

J Pers Med
Marletta S, Baron MM, L'Imperio V, Scarpa A, Caputo A, Perrone G, Merolla F, Malapelle U, Fassan M, Dei Tos AP, Pagni F, Eccher A.   +11 more
europepmc   +1 more source

Systematic protocol to identify 'clinical controls' for paediatric neuroimaging research from clinically acquired brain MRIs. [PDF]

BMJ Open
Zimmerman D, Mandal AS, Jung B, Buczek MJ, Schabdach JM, Karandikar S, Kafadar E, Gardner M, Daniali M, Mercedes L, Kohler S, Abdel-Qader L, Gur RE, Roalf DR, Satterthwaite TD, Williams R, Padmanabhan V, Seidlitz J, White LK, Sotardi S, Schmitt JE, Vossough A, Alexander-Bloch A.   +22 more
europepmc   +1 more source

Applicability Assessment of Technologies for Predictive and Prescriptive Analytics of Nephrology Big Data. [PDF]

Proteomics
Stojanov R, Jovanovik M, Gramatikov S, Mishkovski I, Zdravevski E, Sasanski D, Karapancheva Z, Spasovski G, Vasileska I, Eftimov T, Zhuojun W, Jankowski J, Trajanov D.   +12 more
europepmc   +1 more source

Enhancing Patient-Trial Matching With Large Language Models: A Scoping Review of Emerging Applications and Approaches. [PDF]

JCO Clin Cancer Inform
Chen H, Li X, He X, Chen A, McGill J, Webber EC, Xu H, Liu M, Bian J.   +8 more
europepmc   +1 more source

Leveraging AI to Drive Timely Improvements in Patient Experience Feedback: Algorithm Validation.

JMIR Med Inform
Khanbhai M, Carenzo C, Aryasinghe S, Manton D, Mayer E.   +4 more
europepmc   +1 more source

Question Answering for Electronic Health Records: Scoping Review of Datasets and Models.

J Med Internet Res
Bardhan J, Roberts K, Wang DZ.
europepmc   +1 more source

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Descript-SQL : Enriched Database Descriptions in Text-to-SQL

Text-to-SQL research has developed over several years to make use of Large Language Models (LLMs). One avenue of research is to create models that prompt an existing LLM such as ChatGPT and provide specific context that will assist the LLM in generating correct SQL queries based on a provided database schema and a text question.
openaire   +1 more source

Deep Learning--based Text Classification

ACM Computing Surveys, 2022
Erik Cambria
exaly