AIMC Topic: Electronic Health Records
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GatorCLR: Personalized predictions of patient outcomes on electronic health records using self-supervised contrastive graph representation.
Journal of biomedical informatics
Jun 2, 2025
OBJECTIVE: Recently, there has been growing interest in analyzing large amounts of Electronic Health Record (EHR) data. Patient outcome prediction is a major area of interest in EHR analysis that focuses on predicting the future health status of pati...
Detecting and Remediating Harmful Data Shifts for the Responsible Deployment of Clinical AI Models.
JAMA network open
Jun 2, 2025
IMPORTANCE: Clinical artificial intelligence (AI) systems are susceptible to performance degradation due to data shifts, which can lead to erroneous predictions and potential patient harm. Proactively detecting and mitigating these shifts is crucial ...
Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development.
JMIR medical informatics
Jun 2, 2025
BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.
Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.
Scientific reports
May 28, 2025
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...
Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study.
JMIR medical informatics
May 26, 2025
BACKGROUND: Electronic health records (EHRs) are widely used in health care systems across the United States to help clinicians access patient medical histories in one central location. As medical knowledge expands, clinicians are increasingly using ...
Flexible imputation toolkit for electronic health records.
Scientific reports
May 17, 2025
Missing data in electronic health records (EHRs) poses a significant challenge for analysis. This study introduces Pympute, a comprehensive Python package designed for efficient and robust missing value imputation for EHRs. Pympute's core algorithm, ...
Secondary use of health records for prediction, detection, and treatment planning in the clinical decision support system: a systematic review.
BMC medical informatics and decision making
May 16, 2025
BACKGROUND: This study aims to understand how secondary use of health records can be done for prediction, detection, treatment recommendations, and related tasks in clinical decision support systems.
Automated generation of discharge summaries: leveraging large language models with clinical data.
Scientific reports
May 12, 2025
This study explores the use of open-source large language models (LLMs) to automate generation of German discharge summaries from structured clinical data. The structured data used to produce AI-generated summaries were manually extracted from electr...
[The actual directions of digital development of health care system].
Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
May 8, 2025
The article presents results of analysis of current trends, challenges and prospects of health care digitization. The key directions of digital transformation are considered: telemedicine, implementation of e-medical records, application of AI, Big D...
Anomaly Detection in Electronic Health Records Across Hospital Networks: Integrating Machine Learning With Graph Algorithms.
IEEE journal of biomedical and health informatics
May 6, 2025
In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, the dependability of the health information technology (HIT) ...
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