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Artificial intelligence and machine learning: Definition of terms and current concepts in critical care research.

Journal of critical care
With increasing computing power, artificial intelligence (AI) and machine learning (ML) have prospered, which facilitate the analysis of large datasets, especially those found in critical care. It is important to define these terminologies, to inform...

Report of theĀ HIMSS-SIIM Enterprise Imaging Community Data Standards Evaluation Workgroup: Anatomic Ontology Assessment.

Journal of imaging informatics in medicine
Previously, the lack of a standard body part ontology has been identified as a critical deficiency needed to enable enterprise imaging. This whitepaper aims to provide a comprehensive assessment of anatomical ontologies with the aim of facilitating e...

Data set terminology of deep learning in medicine: a historical review and recommendation.

Japanese journal of radiology
Medicine and deep learning-based artificial intelligence (AI) engineering represent two distinct fields each with decades of published history. The current rapid convergence of deep learning and medicine has led to significant advancements, yet it ha...

Brief Review and Primer of Key Terminology for Artificial Intelligence and Machine Learning in Hypertension.

Hypertension (Dallas, Tex. : 1979)
Recent breakthroughs in artificial intelligence (AI) have caught the attention of many fields, including health care. The vision for AI is that a computer model can process information and provide output that is indistinguishable from that of a human...

Term Candidate Generation to Enrich Clinical Terminologies with Large Language Models.

Studies in health technology and informatics
Annotated language resources derived from clinical routine documentation form an intriguing asset for secondary use case scenarios. In this investigation, we report on how such a resource can be leveraged to identify additional term candidates for a ...

Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology.

Studies in health technology and informatics
Ontology is essential for achieving health information and information technology application interoperability in the biomedical fields and beyond. Traditionally, ontology construction is carried out manually by human domain experts (HDE). Here, we e...

CoRTEx: contrastive learning for representing terms via explanations with applications on constructing biomedical knowledge graphs.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Biomedical Knowledge Graphs play a pivotal role in various biomedical research domains. Concurrently, term clustering emerges as a crucial step in constructing these knowledge graphs, aiming to identify synonymous terms. Due to a lack of ...

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).