AIMC Topic: Electronic Health Records
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Generating Outpatient Progress Notes: A Comparison of Individualized and Generalized Models.
Studies in health technology and informatics
Aug 7, 2025
The increasing documentation workload in medical practice, particularly for clinical notes, has driven the development of AI-driven solutions. This study introduces an AI Doctor Assistant (DA) that generates drafts of outpatient progress notes. The D...
Evaluation of Synthetic Data Generation Methods for Medical Tabular Data: Representation of Distribution Tails.
Studies in health technology and informatics
Aug 7, 2025
Synthetic data generation by Artificial Intelligence (AI) and other means has the potential to share and analyze data while preserving privacy and maintaining statistical characteristics, and various methods have been developed. In medical datasets, ...
Performance of Open-Source Large Language Models to Extract Symptoms from Clinical Notes.
Studies in health technology and informatics
Aug 7, 2025
In this study, we examined how well the open-source foundational large language models (LLMs) can extract symptoms and signs (S&S), along with their corresponding ICD-10 codes, from clinical notes found in the public MTSamples dataset. The dataset co...
Human in the Loop: Embedding Medical Expert Input in Large Language Models for Clinical Applications.
Studies in health technology and informatics
Aug 7, 2025
The state-of-the-art performance of large language models (LLMs) in medical natural language (NLP) tasks, including medical query answering, summarization of clinical notes, and generation of medical reports has led to the development of a large numb...
Ambient Listening in Clinical Practice: Evaluating EPIC Signal Data Before and After Implementation and Its Impact on Physician Workload.
Studies in health technology and informatics
Aug 7, 2025
The widespread adoption of EHRs following the HITECH Act has increased the clinician documentation burden, contributing to burnout. Emerging technologies, such as ambient listening tools powered by generative AI, offer real-time, scribe-like document...
An Ensemble Approach Integrating Retrieval-Augmented Large Language Models and Boosting Algorithms for Enhanced Catatonia Phenotyping.
Studies in health technology and informatics
Aug 7, 2025
A critical first step in using large-scale data to study catatonia is the development of precise phenotyping algorithms that can identify instances of the condition. In this work, we present an ensemble approach that combines retrieval-augmented gene...
Pilot Application of a Large Language Model to Identify Hospitalisation from Unstructured Electronic Health Records in Residential Aged Care Facilities.
Studies in health technology and informatics
Aug 7, 2025
Older people in residential aged care facilities (RACFs) visit hospitals and utilise healthcare services more often than others in the community. Trends in hospitalization rates are essential for designing targeted aged care interventions to reduce p...
Integrating Large Language Models and Machine Learning for Enhanced Catatonia Phenotyping: A Study on Clinical Data from Electronic Health Records.
Studies in health technology and informatics
Aug 7, 2025
Catatonia, a complex syndrome with diagnostic challenges, was studied using a novel approach combining LightGBM and GPT-4 to enhance phenotyping from electronic health record (EHR) data. LightGBM, trained on structured data, achieved superior perform...
Designing a Healthcare Co-Pilot with Generative AI.
Studies in health technology and informatics
Aug 7, 2025
This paper presents our methodology for designing, testing, and evaluating a co-pilot tailored for healthcare professionals working in Spanish-speaking contexts. The co-pilot facilitates efficient access to textual information from clinical notes and...
A Novel Model for Generating Patient Laboratory Test Orders from Admission: Transformer Model Approach.
Studies in health technology and informatics
Aug 7, 2025
There is a growing demand for medical pseudo-data that maintains statistical utility, enabling the analysis of a wide range of medical data without compromising patient privacy. Additionally, there is a growing need for effective sequence prediction ...
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