AIMC Topic: Electronic Health Records
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Can a Large Language Model Interpret Data in the Electronic Health Record to Infer Minimum Clinically Important Difference Achievement of Knee Osteoarthritis Outcome Score-Joint Replacement Score Following Total Knee Arthroplasty?
The Journal of arthroplasty
Jul 1, 2025
BACKGROUND: Obtaining total knee arthroplasty patient-reported outcomes for quality assessment is costly and difficult. We asked whether a large language model (LLM) could interpret electronic health record notes to differentiate patients attaining a...
Development and validation of explainable machine learning models for female hip osteoporosis using electronic health records.
International journal of medical informatics
Jul 1, 2025
BACKGROUND: Hip fractures are associated with reduced mobility, and higher morbidity, mortality, and healthcare costs. Approximately 90% of hip fractures in the elderly are associated with osteoporosis, making it particularly important to screen the ...
Detection of emergency department patients at risk of dementia through artificial intelligence.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 1, 2025
INTRODUCTION: The study aimed to develop and validate the Emergency Department Dementia Algorithm (EDDA) to detect dementia among older adults (65+) and support clinical decision-making in the emergency department (ED).
Artificial intelligence medical scribes in allied health: a solution in search of evidence?
Australian health review : a publication of the Australian Hospital Association
Jun 1, 2025
Artificial intelligence (AI) medical scribes (AI scribes), which ambiently record and transcribe patient-clinician interactions into structured documentation, aim to ameliorate documentation burdens, but their suitability for allied health remains un...
Machine Learning for Clinical Decision Support in the Neonatal Intensive Care Unit.
NeoReviews
Jun 1, 2025
The neonatal intensive care unit (NICU) is a data-rich environment that is an ideal setting for the implementation of machine learning (ML) and artificial intelligence (AI) in clinical decision support (CDS). Despite their potential, ML and AI applic...
Construction and Validation of Artificial Neural Network Model Suggesting Nursing Diagnosis: A Proof-of-Concept Study.
Computers, informatics, nursing : CIN
Jun 1, 2025
There are challenges involving human resource management, as the selection and evaluation processes for nursing diagnostic labels are time-consuming, resulting in an excessive workload. This, in turn, can lead to insufficient attention being given to...
Review learning: Real world validation of privacy preserving continual learning across medical institutions.
Computers in biology and medicine
Jun 1, 2025
When a deep learning model is trained sequentially on different datasets, it often forgets the knowledge learned from previous data, a problem known as catastrophic forgetting. This damages the model's performance on diverse datasets, which is critic...
The potential of artificial intelligence to transform medicine.
Current opinion in pediatrics
Jun 1, 2025
PURPOSE OF REVIEW: Increased incorporation of artificial intelligence in medicine has raised questions regarding how it can enhance efficiency in concert with providing accurate medical information without violating patient privacy. Pediatricians sho...
A transformer-based framework for temporal health event prediction with graph-enhanced representations.
Journal of biomedical informatics
Jun 1, 2025
OBJECTIVE: Deep learning approaches have demonstrated significant potential in predicting temporal health events in recent years. However, existing methods have not fully leveraged the complex interactions among comorbidities and have overlooked imba...
Unsupervised discovery of clinical disease signatures using probabilistic independence.
Journal of biomedical informatics
Jun 1, 2025
OBJECTIVE: This study uses probabilistic independence to disentangle patient-specific sources of disease and their signatures in Electronic Health Record (EHR) data.
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