AIMC Topic: Documentation

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An ontology-based tool for modeling and documenting events in neurosurgery.

BMC medical informatics and decision making
BACKGROUND: Intraoperative neurophysiological monitoring (IOM) plays a pivotal role in enhancing patient safety during neurosurgical procedures. This vital technique involves the continuous measurement of evoked potentials to provide early warnings a...

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology
The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and com...

Can the Administrative Loads of Physicians be Alleviated by AI-Facilitated Clinical Documentation?

Journal of general internal medicine
BACKGROUND: Champions of AI-facilitated clinical documentation have suggested that the emergent technology may decrease the administrative loads of physicians, thereby reducing cognitive burden and forestalling burnout. Explorations of physicians' ex...

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...