Results 81 to 90 of about 3,238,639 (146)

A Self-Controlled Benchmark of Retrieval-Augmented Generation for Large Language Models on Clinical Guideline Questions. [PDF]

Diagnostics (Basel)
Vollmer A, Schorn L, Schrader F, Kübler N, Sproll C, Vollmer M, Singh DD, Saravi B.   +7 more
europepmc   +1 more source

Retrieval-Augmented Generation in Information Science: What Do We Need to Know?

Advances in Knowledge Representation
Information Science is a field that naturally investigates information, that is, contextualized data, its phenomena and interactions, as well as its impacts on society.
Patrícia Nascimento Silva, Daiane Campos Procópio, Danielle Teixeira de Oliveira   +2 more
doaj  

Retrieval-Augmented Generation in Oncology: Promises, Pitfalls, and Early Applications. [PDF]

AI Precis Oncol
Thaker NG, Liu W, Waddle M, Showalter T, Mastroleo F, Luh J, Levitt C, Ning M, Loaiza-Bonilla A, Hong J.   +9 more
europepmc   +1 more source

An automatic consult reply system for therapeutic plasma exchange using retrieval-augmented generation. [PDF]

Vox Sang
Lee JK, Choi S, Park S, Choi Q, Hwang SH, Cho D.   +5 more
europepmc   +1 more source

Accelerating Retrieval-Augmented Generation

An evolving solution to address hallucination and enhance accuracy in large language models (LLMs) is Retrieval-Augmented Generation (RAG), which involves augmenting LLMs with information retrieved from an external knowledge source, such as the web. This
Nouri, Mohammad, Zamani, Hamed, Lee, Sukhan, Quinn, Derrick, Salihu, John, Alian, Mohammad, Patel, Neel, Salemi, Alireza   +7 more
core   +1 more source

EyeRAG: graph retrieval-augmented generation for safe and accurate clinical dialogue in ophthalmology. [PDF]

NPJ Digit Med
Zhao K, Kang D, Yu T, Yao R, Han W, Liang K, Agrawal R, Grzybowski A, Jin K.   +8 more
europepmc   +1 more source

A framework for extraction of clinical information from radiological mammography reports using large language models and retrieval augmented generation. [PDF]

BMC Med Inform Decis Mak
Godoy E, Ferrari J, Lazo S, Pacheco C, Mellado D, Saez A, Chabert S, Salas R.   +7 more
europepmc   +1 more source

Retrieval-Augmented Generation for Predicting Cellular Responses to Gene Perturbation

Predicting how cells respond to genetic perturbations is fundamental to understanding gene function, disease mechanisms, and therapeutic development. While recent deep learning approaches have shown promise in modeling single-cell perturbation responses,
Andrea Giuseppe Di Francesco, Pietro Lio, Andrea Rubbi   +2 more
core  

Enhancing antimicrobial stewardship using a retrieval-augmented generation large language model for infectious disease management. [PDF]

Einstein (Sao Paulo)
Morales H, Rocha C, Dalmazo LMT, Takara LA, Cichelero M, Guerra B, Andrade-Silva J, Tuma P, Silva Júnior M.   +8 more
europepmc   +1 more source

Terminologie und Retrieval- Augmented Generation (TermRAG)

In this article, we introduce the concepts of Retrieval-Augmented Generation (RAG) and TermRAG. RAG is a technique that Combines the capabilities of generative language models with information-retrieval methods for more precise and reliable output ...
Suchowolec, Karolina, Lang, Christian
core   +1 more source