AIMC Topic: Electronic Health Records

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Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2025
OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores, a widely adopted standard for cognitive assessment in patients with Alzheimer's disease, using natural language processing (NLP) and machine learnin...
Natural Language Processing Alzheimer Disease Mental Status and Dementia Tests Aged, 80 and over Male Machine Learning Phenotype Female Aged Electronic Health Records Humans
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Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2025
OBJECTIVES: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented in narrative clinical notes r...
Mental Disorders Electronic Health Records Social Support Humans Algorithms Data Mining Natural Language Processing Social Isolation
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Secure messaging telehealth billing in the digital age: moving beyond time-based metrics.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2025
OBJECTIVE: We proposed adopting billing models for secure messaging (SM) telehealth services that move beyond time-based metrics, focusing on the complexity and clinical expertise involved in patient care.
Electronic Health Records Humans Telemedicine Computer Security Machine Learning
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Reducing diagnostic delays in acute hepatic porphyria using health records data and machine learning.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2025
BACKGROUND: Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of 15 years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recogn...
Young Adult Adult Male Electronic Health Records Female Adolescent Delayed Diagnosis Referral and Consultation Middle Aged Porphobilinogen Synthase Humans Porphyrias, Hepatic Machine Learning
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Machine learning to predict adverse drug events based on electronic health records: a systematic review and meta-analysis.

The Journal of international medical research Dec 1, 2024
OBJECTIVE: This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse drug events (ADEs) using electronic health record (EHR) data.
Electronic Health Records Risk Factors Drug-Related Side Effects and Adverse Reactions Humans Support Vector Machine ROC Curve Machine Learning Area Under Curve
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Artificial intelligence-aided data mining of medical records for cancer detection and screening.

The Lancet. Oncology Dec 1, 2024
The application of artificial intelligence methods to electronic patient records paves the way for large-scale analysis of multimodal data. Such population-wide data describing deep phenotypes composed of thousands of features are now being leveraged...
Early Detection of Cancer Data Mining Electronic Health Records Neoplasms Humans Artificial Intelligence
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Detection of suicidality from medical text using privacy-preserving large language models.

The British journal of psychiatry : the journal of mental science Dec 1, 2024
BACKGROUND: Attempts to use artificial intelligence (AI) in psychiatric disorders show moderate success, highlighting the potential of incorporating information from clinical assessments to improve the models. This study focuses on using large langua...
Artificial Intelligence Mental Disorders Sensitivity and Specificity Suicide Electronic Health Records Humans Natural Language Processing
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Fair prediction of 2-year stroke risk in patients with atrial fibrillation.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
Black or African American Racial Groups Stroke Atrial Fibrillation Aged Male Machine Learning Risk Factors Risk Assessment Humans Electronic Health Records Middle Aged ROC Curve Female
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Handwritten Data Extraction Using OpenAI ChatGPT4o and Robotic Process Automation.

Studies in health technology and informatics Nov 22, 2024
This paper proposes to create an Robotic Process Automation style application that can digitalize and extract data from handwritten medical forms. The RPA robot uses OpenAI ChatGPT4o model to extract handwritten medical data and transform it into typ...
Handwriting Electronic Health Records Humans Robotics Machine Learning Information Storage and Retrieval
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Generating Synthetic Healthcare Dialogues in Emergency Medicine Using Large Language Models.

Studies in health technology and informatics Nov 22, 2024
Natural Language Processing (NLP) has shown promise in fields like radiology for converting unstructured into structured data, but acquiring suitable datasets poses several challenges, including privacy concerns. Specifically, we aim to utilize Large...
Natural Language Processing Humans Electronic Health Records Emergency Medicine
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