AI Medical Compendium Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 151 to 160 of 493 articles

Using large language model to guide patients to create efficient and comprehensive clinical care message.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study aims to investigate the feasibility of using Large Language Models (LLMs) to engage with patients at the time they are drafting a question to their healthcare providers, and generate pertinent follow-up questions that the patien...

Cumulus: a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access app...

Constructing knowledge: the role of AI in medical learning.

Journal of the American Medical Informatics Association : JAMIA
The integration of large language models (LLMs) like ChatGPT into medical education presents potential benefits and challenges. These technologies, aligned with constructivist learning theories, could potentially enhance critical thinking and problem...

A general framework for developing computable clinical phenotype algorithms.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machi...

Deep learning with noisy labels in medical prediction problems: a scoping review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Medical research faces substantial challenges from noisy labels attributed to factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of label noise management remains limited, and label noise is lar...

Acute myocardial infarction prognosis prediction with reliable and interpretable artificial intelligence system.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Predicting mortality after acute myocardial infarction (AMI) is crucial for timely prescription and treatment of AMI patients, but there are no appropriate AI systems for clinicians. Our primary goal is to develop a reliable and interpreta...

Strengthening the use of artificial intelligence within healthcare delivery organizations: balancing regulatory compliance and patient safety.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Surface the urgent dilemma that healthcare delivery organizations (HDOs) face navigating the US Food and Drug Administration (FDA) final guidance on the use of clinical decision support (CDS) software.

Toward a unified understanding of drug-drug interactions: mapping Japanese drug codes to RxNorm concepts.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Linking information on Japanese pharmaceutical products to global knowledge bases (KBs) would enhance international collaborative research and yield valuable insights. However, public access to mappings of Japanese pharmaceutical products...

A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic ...

Comparing natural language processing representations of coded disease sequences for prediction in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing (NLP) algorithms are increasingly being applied to obtain unsupervised representations of electronic health record (EHR) data, but their comparative performance at predicting clinical endpoints remains unclear. ...