AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Electronic Health Records

Showing 271 to 280 of 2332 articles

Clear Filters

Recognition of Chinese Electronic Medical Records for Rehabilitation Robots: Information Fusion Classification Strategy.

Sensors (Basel, Switzerland)
Named entity recognition is a critical task in the electronic medical record management system for rehabilitation robots. Handwritten documents often contain spelling errors and illegible handwriting, and healthcare professionals frequently use diffe...

Special supplement issue on quality assurance and enrichment of biological and biomedical ontologies and terminologies.

BMC medical informatics and decision making
Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains, facilitating data integration, interoperability, and semantic understanding across diverse applications. However, the quality assurance and enrichme...

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...

Multimodal fusion network for ICU patient outcome prediction.

Neural networks : the official journal of the International Neural Network Society
Over the past decades, massive Electronic Health Records (EHRs) have been accumulated in Intensive Care Unit (ICU) and many other healthcare scenarios. The rich and comprehensive information recorded presents an exceptional opportunity for patient ou...

The potential for large language models to transform cardiovascular medicine.

The Lancet. Digital health
Cardiovascular diseases persist as the leading cause of death globally and their early detection and prediction remain a major challenge. Artificial intelligence (AI) tools can help meet this challenge as they have considerable potential for early di...

From admission to discharge: a systematic review of clinical natural language processing along the patient journey.

BMC medical informatics and decision making
BACKGROUND: Medical text, as part of an electronic health record, is an essential information source in healthcare. Although natural language processing (NLP) techniques for medical text are developing fast, successful transfer into clinical practice...

A neural network approach to predict opioid misuse among previously hospitalized patients using electronic health records.

PloS one
Can Electronic Health Records (EHR) predict opioid misuse in general patient populations? This research trained three backpropagation neural networks to explore EHR predictors using existing patient data. Model 1 used patient diagnosis codes and was ...

AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: For medical diagnosis, clinicians typically begin with a patient's chief concerns, followed by questions about symptoms and medical history, physical examinations, and requests for necessary auxiliary examinations to gather comprehensive ...

Multi-task heterogeneous graph learning on electronic health records.

Neural networks : the official journal of the International Neural Network Society
Learning electronic health records (EHRs) has received emerging attention because of its capability to facilitate accurate medical diagnosis. Since the EHRs contain enriched information specifying complex interactions between entities, modeling EHRs ...