AIMC Topic: Electronic Health Records
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MISTIC: a novel approach for metastasis classification in Italian electronic health records using transformers.
BMC medical informatics and decision making
Apr 10, 2025
BACKGROUND: Analysis of Electronic Health Records (EHRs) is crucial in real-world evidence (RWE), especially in oncology, as it provides valuable insights into the complex nature of the disease. The implementation of advanced techniques for automated...
Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.
JMIR medical informatics
Apr 10, 2025
BACKGROUND: Congestive heart failure (CHF) is a common cause of hospital admissions. Medical records contain valuable information about CHF, but manual chart review is time-consuming. Claims databases (using International Classification of Diseases [...
Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.
JMIR medical informatics
Apr 9, 2025
BACKGROUND: Valuable insights gathered by clinicians during their inquiries and documented in textual reports are often unavailable in the structured data recorded in electronic health records (EHRs).
Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.
Clinical pharmacology and therapeutics
Apr 8, 2025
Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated. This study aimed to establish a natural language processing (NLP)-based validation framework to ev...
Low-cost algorithms for clinical notes phenotype classification to enhance epidemiological surveillance: A case study.
Journal of biomedical informatics
Apr 8, 2025
OBJECTIVE: Our study aims to enhance epidemic intelligence through event-based surveillance in an emerging pandemic context. We classified electronic health records (EHRs) from La Rioja, Argentina, focusing on predicting COVID-19-related categories i...
Year 2023 in Biomedical Natural Language Processing: a Tribute to Large Language Models and Generative AI.
Yearbook of medical informatics
Apr 8, 2025
OBJECTIVES: This synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best papers and the two best papers of this ...
Natural Language Processing for Digital Health in the Era of Large Language Models.
Yearbook of medical informatics
Apr 8, 2025
OBJECTIVES: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize...
Advancing Clinical Information Systems: Harnessing Telemedicine, Data Science, and AI for Enhanced and More Precise Healthcare Delivery.
Yearbook of medical informatics
Apr 8, 2025
OBJECTIVE: In this synopsis, the editors of the Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics overview recent research and propose a selection of best papers published in 2023 in the CIS field.
Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.
Renal failure
Apr 7, 2025
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD prediction are urgently needed. This study aimed to set up DKD risk prediction models based on machine lear...
Assessing Patient-Reported Satisfaction With Care and Documentation Time in Primary Care Through AI-Driven Automatic Clinical Note Generation: Protocol for a Proof-of-Concept Study.
JMIR research protocols
Apr 7, 2025
BACKGROUND: Relisten is an artificial intelligence (AI)-based software developed by Recog Analytics that improves patient care by facilitating more natural interactions between health care professionals and patients. This tool extracts relevant infor...
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