AIMC Topic: Documentation

Clear Filters Showing 31 to 40 of 173 articles

Equity in Using Artificial Intelligence Mortality Predictions to Target Goals of Care Documentation.

Journal of general internal medicine
BACKGROUND: Artificial intelligence (AI) algorithms are increasingly used to target patients with elevated mortality risk scores for goals-of-care (GOC) conversations.

Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.

Perspectives in health information management
Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial Intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to underst...

Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.

PloS one
OBJECTIVE: To establish whether or not a natural language processing technique could identify two common inpatient neurosurgical comorbidities using only text reports of inpatient head imaging.

Use of natural language processing to uncover racial bias in obstetrical documentation.

Clinical imaging
Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinical documentation to be integrated in ways that facilitate data analysis, data interpretation and formation of individualized medical and obstetrical ca...

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

Journal of biomedical informatics
OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different dise...

Harnessing the Power of Generative AI for Clinical Summaries: Perspectives From Emergency Physicians.

Annals of emergency medicine
STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and professional burnout. The advent of generative artificial intelligence language models presents a promising solution. The perspective of clinicians may contr...

Transformer Models in Healthcare: A Survey and Thematic Analysis of Potentials, Shortcomings and Risks.

Journal of medical systems
Large Language Models (LLMs) such as General Pretrained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT), which use transformer model architectures, have significantly advanced artificial intelligence and natural l...

Bolstering Advance Care Planning Measurement Using Natural Language Processing.

Journal of palliative medicine
Despite its growth as a clinical activity and research topic, the complex dynamic nature of advance care planning (ACP) has posed serious challenges for researchers hoping to quantitatively measure it. Methods for measurement have traditionally depen...