AIMC Topic: Electronic Health Records
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Utilising Natural Language Processing to Identify Brain Tumor Patients for Clinical Trials: Development and Initial Evaluation.
World neurosurgery
Mar 18, 2025
BACKGROUND: Identifying patients eligible for clinical trials through eligibility screening is time and resource-intensive. Natural Language Processing (NLP) models may enhance clinical trial screening by extracting data from Electronic Health Record...
Enhancing Patient Outcome Prediction Through Deep Learning With Sequential Diagnosis Codes From Structured Electronic Health Record Data: Systematic Review.
Journal of medical Internet research
Mar 18, 2025
BACKGROUND: The use of structured electronic health records in health care systems has grown rapidly. These systems collect huge amounts of patient information, including diagnosis codes representing temporal medical history. Sequential diagnostic in...
Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.
Journal of the American College of Surgeons
Mar 17, 2025
BACKGROUND: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on the det...
Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.
Cerebrovascular diseases extra
Mar 17, 2025
INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart review to screen for thrombolysis contraindications may be time-consuming and prone to errors. We developed and tested a large language model (LLM)-bas...
How to leverage large language models for automatic ICD coding.
Computers in biology and medicine
Mar 14, 2025
ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healthcare tasks such as health expense claims, insurance claims, and disease research. Manual ICD coding is time-consuming and prone to errors, increasing...
Deep representation learning for clustering longitudinal survival data from electronic health records.
Nature communications
Mar 14, 2025
Precision medicine requires accurate identification of clinically relevant patient subgroups. Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subgroups. However, many existing ...
Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.
Journal of the American Heart Association
Mar 13, 2025
Electronic health records (EHR) have revolutionized cardiovascular disease (CVD) research by enabling comprehensive, large-scale, and dynamic data collection. Integrating EHR data with advanced analytical methods, including artificial intelligence (A...
Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.
JMIR medical informatics
Mar 12, 2025
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...
Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.
Diabetes, obesity & metabolism
Mar 11, 2025
AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large dataset...
Non-Face-to-Face Services in Neurologic Care.
Seminars in neurology
Mar 10, 2025
Neurologists in ambulatory settings struggle with low appointment availability and increased work related to patient care outside of clinic visits. Neurologists can better meet these demands using asynchronous or non-face-to-face care options. Specif...
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