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

Showing 1 to 10 of 493 articles

A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis.

Journal of the American Medical Informatics Association : JAMIA May 7, 2025
BACKGROUND: Automated data extraction from echocardiography reports could facilitate large-scale registry creation and clinical surveillance of valvular heart diseases (VHD). We evaluated the performance of open-source large language models (LLMs) gu...
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CDEMapper: enhancing National Institutes of Health common data element use with large language models.

Journal of the American Medical Informatics Association : JAMIA May 7, 2025
OBJECTIVE: Common Data Elements (CDEs) standardize data collection and sharing across studies, enhancing data interoperability and improving research reproducibility. However, implementing CDEs presents challenges due to the broad range and variety o...
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Adoption of artificial intelligence in healthcare: survey of health system priorities, successes, and challenges.

Journal of the American Medical Informatics Association : JAMIA May 5, 2025
IMPORTANCE: The US healthcare system faces significant challenges, including clinician burnout, operational inefficiencies, and concerns about patient safety. Artificial intelligence (AI), particularly generative AI, has the potential to address thes...
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Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.

Journal of the American Medical Informatics Association : JAMIA Aug 7, 2016
OBJECTIVE: Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, a...
Male Middle Aged ROC Curve Female Aged Natural Language Processing Hypertension Blood Pressure Determination Information Storage and Retrieval Algorithms Humans Phenotype Clinical Coding Machine Learning Electronic Health Records
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Learning temporal rules to forecast instability in continuously monitored patients.

Journal of the American Medical Informatics Association : JAMIA Jun 6, 2016
Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appea...
Humans Machine Learning Forecasting Respiratory Insufficiency Time Factors Cardiovascular System Monitoring, Physiologic Hospital Units
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Learning disease relationships from clinical drug trials.

Journal of the American Medical Informatics Association : JAMIA May 17, 2016
OBJECTIVE: Our objective is to test the limits of the assumption that better learning from data in medicine requires more granular data. We hypothesize that clinical trial metadata contains latent scientific, clinical, and regulatory expert knowledge...
Drug Evaluation Vocabulary, Controlled Clinical Trials as Topic Machine Learning Drug Therapy Disease Area Under Curve Metadata Medical Subject Headings Humans Data Mining
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Learning statistical models of phenotypes using noisy labeled training data.

Journal of the American Medical Informatics Association : JAMIA May 12, 2016
OBJECTIVE: Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled traini...
Logistic Models Models, Statistical Myocardial Infarction Electronic Health Records Diabetes Mellitus, Type 2 Vocabulary, Controlled Medical Informatics Computing Humans Algorithms Phenotype Machine Learning
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Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature.

Journal of the American Medical Informatics Association : JAMIA Apr 27, 2016
OBJECTIVE: Identifying disease-mutation relationships is a significant challenge in the advancement of precision medicine. The aim of this work is to design a tool that automates the extraction of disease-related mutations from biomedical text to adv...
Databases as Topic PubMed Data Mining Breast Neoplasms Male Precision Medicine Prostatic Neoplasms Humans Female Mutation Computational Biology Machine Learning
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Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department.

Journal of the American Medical Informatics Association : JAMIA Apr 27, 2016
OBJECTIVE: (1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-w...
Patient Participation Patient Acceptance of Health Care Hospitals, Pediatric Humans Clinical Trials as Topic Machine Learning Male Child Emergency Service, Hospital Algorithms Female
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Electronic medical record phenotyping using the anchor and learn framework.

Journal of the American Medical Informatics Association : JAMIA Apr 23, 2016
BACKGROUND: Electronic medical records (EMRs) hold a tremendous amount of information about patients that is relevant to determining the optimal approach to patient care. As medicine becomes increasingly precise, a patient's electronic medical record...
Humans Machine Learning Electronic Health Records Natural Language Processing Phenotype Databases as Topic Decision Making, Computer-Assisted Area Under Curve Emergency Service, Hospital
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