AIMC Topic: Information Storage and Retrieval

Clear Filters Showing 551 to 560 of 738 articles

RAMIE: retrieval-augmented multi-task information extraction with large language models on dietary supplements.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop an advanced multi-task large language model (LLM) framework for extracting diverse types of information about dietary supplements (DSs) from clinical records.

Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning over large text so...

Evaluating a large language model's ability to answer clinicians' requests for evidence summaries.

Journal of the Medical Library Association : JMLA
OBJECTIVE: This study investigated the performance of a generative artificial intelligence (AI) tool using GPT-4 in answering clinical questions in comparison with medical librarians' gold-standard evidence syntheses.

Leveraging AI tools for streamlined library event planning: a case study from Lane Medical Library.

Journal of the Medical Library Association : JMLA
Health sciences and hospital libraries often face challenges in planning and organizing events due to limited resources and staff. At Stanford School of Medicine's Lane Library, librarians turned to artificial intelligence (AI) tools to address this ...

Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from syntheses and databases.

PloS one
Wise use of evidence to support efficient conservation action is key to tackling biodiversity loss with limited time and resources. Evidence syntheses provide key recommendations for conservation decision-makers by assessing and summarising evidence,...

A comparative analysis of large language models versus traditional information extraction methods for real-world evidence of patient symptomatology in acute and post-acute sequelae of SARS-CoV-2.

PloS one
BACKGROUND: Patient symptoms, crucial for disease progression and diagnosis, are often captured in unstructured clinical notes. Large language models (LLMs) offer potential advantages in extracting patient symptoms compared to traditional rule-based ...

Handwritten Data Extraction Using OpenAI ChatGPT4o and Robotic Process Automation.

Studies in health technology and informatics
This paper proposes to create an Robotic Process Automation style application that can digitalize and extract data from handwritten medical forms. The RPA robot uses OpenAI ChatGPT4o model to extract handwritten medical data and transform it into typ...

FHIR-Based Arden Syntax Compiler for Clinical Decision Support.

Studies in health technology and informatics
The Arden Syntax is a language designed for the encoding of medical knowledge into clinical decision support systems. Its evolution is overseen by Health Level 7. A significant enhancement in its new version 3.0 is the incorporation of FHIR for data ...

Utilizing RAG and GPT-4 for Extraction of Substance Use Information from Clinical Notes.

Studies in health technology and informatics
This research investigates the application of a hybrid Retrieval-Augmented Generation (RAG) and Generative Pre-trained Transformer (GPT) pipeline for extracting and categorizing substance use information from unstructured clinical notes. The aim is t...

Representation of Social Determinants of Health terminology in medical subject headings: impact of added terms.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To enhance and evaluate the quality of PubMed search results for Social Determinants of Health (SDoH) through the addition of new SDoH terms to Medical Subject Headings (MeSH).