AI Medical Compendium Topic

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Systematic Reviews as Topic

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Extractive text summarization system to aid data extraction from full text in systematic review development.

Journal of biomedical informatics
OBJECTIVES: Extracting data from publication reports is a standard process in systematic review (SR) development. However, the data extraction process still relies too much on manual effort which is slow, costly, and subject to human error. In this s...

SWIFT-Review: a text-mining workbench for systematic review.

Systematic reviews
BACKGROUND: There is growing interest in using machine learning approaches to priority rank studies and reduce human burden in screening literature when conducting systematic reviews. In addition, identifying addressable questions during the problem ...

Collating the knowledge base for core outcome set development: developing and appraising the search strategy for a systematic review.

BMC medical research methodology
BACKGROUND: The COMET (Core Outcome Measures in Effectiveness Trials) Initiative is developing a publicly accessible online resource to collate the knowledge base for core outcome set development (COS) and the applied work from different health condi...

Machine learning-assisted literature screening for a medication-use process-related systematic review.

American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
PURPOSE: This article summarizes a novel methodology of applying machine learning (ML) algorithms trained with external training data to assist with article screening for 2 annual review series related to the medication-use process (MUP) generally an...

High-performance automated abstract screening with large language model ensembles.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: screening is a labor-intensive component of systematic review involving repetitive application of inclusion and exclusion criteria on a large volume of studies. We aimed to validate large language models (LLMs) used to automate abstract sc...

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...

Automated tools for systematic review screening methods: an application of machine learning for sexual orientation and gender identity measurement in health research.

Journal of the Medical Library Association : JMLA
OBJECTIVE: Sexual and gender minority (SGM) populations experience health disparities compared to heterosexual and cisgender populations. The development of accurate, comprehensive sexual orientation and gender identity (SOGI) measures is fundamental...

A question-answering framework for automated abstract screening using large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This paper aims to address the challenges in abstract screening within systematic reviews (SR) by leveraging the zero-shot capabilities of large language models (LLMs).