AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
Annotated language resources are essential for supervised machine learning methods. In the clinical domain, such data sets can boost use-case specific natural language processing services. In this work, we have analyzed a clinical problem list table ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
Large Language Models (LLMs) have revolutionized various sectors, including healthcare where they are employed in diverse applications. Their utility is particularly significant in the context of rare diseases, where data scarcity, complexity, and sp...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
Healthcare providers learn continuously, but better support for provider learning is needed as new biomedical knowledge is produced at an increasing rate alongside widespread use of EHR data for clinical performance measurement. Precision feedback is...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
In the evolving landscape of clinical Natural Language Generation (NLG), assessing abstractive text quality remains challenging, as existing methods often overlook generative task complexities. This work aimed to examine the current state of automate...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic resistance challenges these achievements and emphasizes the need for innovative stewardship strategies. In this study, we developed machine learning m...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
This study compared large language models (LLMs) and Bidirectional Encoder Representations from Transformers (BERT) models in identifying medication names, routes, and frequencies from publicly available free-text ophthalmology progress notes of 480 ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
The increase in utilization of patient portal messages has imposed a considerable burden on healthcare providers, contributing to an increased incidence of provider burnout. This study introduces a framework for leveraging Large Language Models (LLMs...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
In this study, we explore a natural language processing (NLP) algorithm's capacity to identify proximal but distinct suicide attempt (SA) events compared to diagnostic code-based approaches. This study used an NLP algorithm with high precision in ide...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
This study evaluates the utility of machine learning (ML) algorithms in early forecasting of total symptom score changes from daily self-reports of 339 chemotherapy patients. The dataset comprised 12 specific symptoms, with severity and distress for ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
In the classroom, artificial intelligence techniques help automate student behavior analysis, and teachers are able to understand students' class status more effectively. We developed an intelligent method for classroom behavior analysis by building ...