AIMC Topic: Electronic Health Records
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Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study.
JMIR medical informatics
Jul 24, 2025
BACKGROUND: By analyzing electronic health record snapshots of similar patients, physicians can proactively predict disease onsets, customize treatment plans, and anticipate patient-specific trajectories. However, the modeling of electronic health re...
Improving Large Language Models' Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation.
JMIR medical informatics
Jul 24, 2025
BACKGROUND: The American Medical Association recommends that electronic health record (EHR) notes, often dense and written in nuanced language, be made readable for patients and laypeople, a practice we refer to as the simplification of discharge not...
Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.
Scientific reports
Jul 23, 2025
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...
Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.
JMIR human factors
Jul 23, 2025
BACKGROUND: Primary care providers (PCPs) face significant burnout due to increasing administrative and documentation demands, contributing to job dissatisfaction and impacting care quality. Artificial intelligence (AI) scribes have emerged as potent...
Early detection of ICU-acquired infections using high-frequency electronic health record data.
BMC medical informatics and decision making
Jul 21, 2025
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...
Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records.
Scientific reports
Jul 21, 2025
Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing ...
Multicriteria Optimization of Language Models for Heart Failure With Preserved Ejection Fraction Symptom Detection in Spanish Electronic Health Records: Comparative Modeling Study.
Journal of medical Internet research
Jul 17, 2025
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a major clinical manifestation of cardiac amyloidosis, a condition frequently underdiagnosed due to its nonspecific symptomatology. Electronic health records (EHRs) offer a promisi...
Application of artificial intelligence to electronic health record data in long-term care facilities: a scoping review protocol.
BMJ open
Jul 16, 2025
INTRODUCTION: Although artificial intelligence (AI) has been widely applied to electronic health record (EHR) data in hospital environments, its use in long-term care (LTC) facilities remains unexplored. Limited information technology infrastructure ...
Development and external validation of a machine learning model for predicting drug-induced immune thrombocytopenia in a real-world hospital cohort.
BMC medical informatics and decision making
Jul 15, 2025
BACKGROUND: Drug-induced immune thrombocytopenia (DITP) is a rare but potentially life-threatening adverse drug reaction, often underrecognized due to its nonspecific presentation and the lack of real-time diagnostic tools. Early identification of at...
EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation.
BMC bioinformatics
Jul 10, 2025
BACKGROUND: Drug recommendation is a crucial application of artificial intelligence in medical practice. Although many models have been proposed to solve this task, two challenges remain unresolved: (i) most existing models use all historical visits ...
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