Managing chronic diseases requires ongoing monitoring of disease activity and therapeutic responses to optimize treatment plans. With the growing availability of disease-modifying therapies, it is crucial to investigate comparative effectiveness and ...
Predicting treatment response is an important problem in real-world applications, where the heterogeneity of the treatment response remains a significant challenge in practice. Unsupervised machine learning methods have been proposed to address this ...
BACKGROUND: Synthetic electronic health records (EHRs) generated by large language models (LLMs) offer potential for clinical education and model training while addressing privacy concerns. However, performance variations and demographic biases in th...
In a recent study, the effectiveness of GPT-4 Omni in transforming lobectomy surgical records into structured data across multiple languages was explored. The aim was to improve both efficiency and accuracy in documenting thoracic surgical oncology p...
Alzheimer's & dementia : the journal of the Alzheimer's Association
May 1, 2025
INTRODUCTION: Identifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health reco...
IMPORTANCE: The increase of electronic health record (EHR) work negatively impacts clinician well-being. One potential solution is incorporating an ambient artificial intelligence (AI) documentation platform.
IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into pra...
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVE: This study evaluates the integration of electronic health records (EHRs) and natural language processing (NLP) with large language models (LLMs) to enhance healthcare data management and patient care, focusing on using advanced language mo...
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVES: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.