AIMC Topic: Evidence-Based Medicine

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Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not com...

The present and future of lung cancer screening: latest evidence.

Future oncology (London, England)
Lung cancer is the leading cause of cancer-related mortality worldwide. Early lung cancer detection improves lung cancer-related mortality and survival. This report summarizes presentations and panel discussions from a webinar, "The Present and Futur...

Large Language Model-Assisted Systematic Review: Validation Based on Cochrane Review Data.

Studies in health technology and informatics
Large Language Models (LLMs) offer potential for automating systematic reviews, a labor-intensive process in evidence-based medicine. We evaluated GPT-4o, GPT-4o-mini, and Llama 3.1:8B on abstract screening and risk of bias assessment using 12 Cochra...

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.

Towards Autonomous Living Meta-Analyses: A Framework for Automation of Systematic Review and Meta-Analyses.

Studies in health technology and informatics
Systematic review and meta-analysis constitute a staple of evidence-based medicine, an obligatory step in developing the guideline and recommendation document. It is a formalized process aiming at extracting and summarizing knowledge from the publish...

Clinical Evaluation of Artificial Intelligence-Enabled Interventions.

Investigative ophthalmology & visual science
Artificial intelligence (AI) health technologies are increasingly available for use in real-world care. This emerging opportunity is accompanied by a need for decision makers and practitioners across healthcare systems to evaluate the safety and effe...

Exploring the Value of MRI Measurement of Hippocampal Volume for Predicting the Occurrence and Progression of Alzheimer's Disease Based on Artificial Intelligence Deep Learning Technology and Evidence-Based Medicine Meta-Analysis.

Journal of Alzheimer's disease : JAD
BACKGROUND: Alzheimer's disease (AD), a major dementia cause, lacks effective treatment. MRI-based hippocampal volume measurement using artificial intelligence offers new insights into early diagnosis and intervention in AD progression.

Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers.

Cell reports. Medicine
Current and future healthcare professionals are generally not trained to cope with the proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum that caters to variable baseline knowledge and skills, clinicians ma...

The Quality and Utility of Artificial Intelligence in Patient Care.

Deutsches Arzteblatt international
BACKGROUND: Artificial intelligence (AI) is increasingly being used in patient care. In the future, physicians will need to understand not only the basic functioning of AI applications, but also their quality, utility, and risks.

AI-generated text may have a role in evidence-based medicine.

Nature medicine
vidence-based medicine (EBM) requires the retrieval and ranking of relevant evidence by epistemological strength, to identify the most appropriate evidence to inform guidelines and policies, with a preference for robust evidence from randomized clini...