AIMC Topic: Information Storage and Retrieval

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An Integrated AI Cloud Sharing Framework for Predictive AI and Generative AI in Healthcare.

Studies in health technology and informatics
In 2019, Chi Mei Hospital built a private cloud AI service framework, incorporating HIS interface web service, data retrieval web service, and AI web service. Numerous Predictive AI (PAI) applications were deployed successfully. By 2023, the hospital...

Retrieval Augmented Generation: What Works and Lessons Learned.

Studies in health technology and informatics
Retrieval Augmented Generation has been shown to improve the output of large language models (LLMs) by providing context to the question or scenario posed to the model. We have tried a series of experiments to understand how best to improve the perfo...

Large-scale information retrieval and correction of noisy pharmacogenomic datasets through residual thresholded deep matrix factorization.

Briefings in bioinformatics
Pharmacogenomics studies are attracting an increasing amount of interest from researchers in precision medicine. The advances in high-throughput experiments and multiplexed approaches allow the large-scale quantification of drug sensitivities in mole...

Enhancing Large Language Models with Retrieval-Augmented Generation: A Radiology-Specific Approach.

Radiology. Artificial intelligence
Retrieval-augmented generation (RAG) is a strategy to improve the performance of large language models (LLMs) by providing an LLM with an updated corpus of knowledge that can be used for answer generation in real time. RAG may improve LLM performance...

Open-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters.

Radiology. Artificial intelligence
Purpose To develop and evaluate an automated system for extracting structured clinical information from unstructured radiology and pathology reports using open-weight language models (LMs) and retrieval-augmented generation (RAG) and to assess the ef...

Integrating PICO principles into generative artificial intelligence prompt engineering to enhance information retrieval for medical librarians.

Journal of the Medical Library Association : JMLA
Prompt engineering, an emergent discipline at the intersection of Generative Artificial Intelligence (GAI), library science, and user experience design, presents an opportunity to enhance the quality and precision of information retrieval. An innovat...

Enhancing systematic literature reviews with generative artificial intelligence: development, applications, and performance evaluation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We developed and validated a large language model (LLM)-assisted system for conducting systematic literature reviews in health technology assessment (HTA) submissions.

Collaborative large language models for automated data extraction in living systematic reviews.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Data extraction from the published literature is the most laborious step in conducting living systematic reviews (LSRs). We aim to build a generalizable, automated data extraction workflow leveraging large language models (LLMs) that mimic...

Improving large language model applications in biomedicine with retrieval-augmented generation: a systematic review, meta-analysis, and clinical development guidelines.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The objectives of this study are to synthesize findings from recent research of retrieval-augmented generation (RAG) and large language models (LLMs) in biomedicine and provide clinical development guidelines to improve effectiveness.

Semi-supervised learning from small annotated data and large unlabeled data for fine-grained Participants, Intervention, Comparison, and Outcomes entity recognition.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Extracting PICO elements-Participants, Intervention, Comparison, and Outcomes-from clinical trial literature is essential for clinical evidence retrieval, appraisal, and synthesis. Existing approaches do not distinguish the attributes of P...