AI Medical Compendium Journal:
AMIA ... Annual Symposium proceedings. AMIA Symposium

Showing 11 to 20 of 377 articles

Emulation of a Target Trial to Estimate the Effect of Selective Serotonin Reuptake Inhibitors on the Development of Antimicrobial-Resistant Infections using Electronic Health Record Data and Causal Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Antimicrobial resistance is a significant public health concern. The use of selective serotonin reuptake inhibitors (SSRIs), medications commonly prescribed to treat depression, anxiety, and other psychiatric disorders, is increasing. Previous in vit...

A Novel Sentence Transformer-based Natural Language Processing Approach for Schema Mapping of Electronic Health Records to the OMOP Common Data Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Mapping electronic health records (EHR) data to common data models (CDMs) enables the standardization of clinical records, enhancing interoperability and enabling large-scale, multi-centered clinical investigations. Using 2 large publicly available d...

Unlocking Early Cancer Detection: Leveraging Machine Learning in Cell-Free DNA Analysis for Precision Oncology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study introduces a groundbreaking approach to early cancer detection through the analysis of cell-free DNA (cfDNA), utilizing machine learning algorithms to navigate the complexities of low circulating tumor DNA (ctDNA) fractions and genetic het...

Derivation and Experimental Performance of Standard and Novel Uncertainty Calibration Techniques.

AMIA ... Annual Symposium proceedings. AMIA Symposium
To aid in the transparency of state-of-the-art machine learning models, there has been considerable research performed in uncertainty quantification (UQ). UQ aims to quantify what a model does not know by measuring variation of the model under stocha...

Neural Mosaics: Detecting Aberrant Brain Interactions using Algebraic Topology and Generative Artificial Intelligence.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Epilepsy affects over 50 million persons worldwide, with less than 50% achieving long-term success following surgery. Traditional electrophysiology signal-based seizure detection methods are resource-intensive, laborious, and overlook multifocal brai...

Towards Optimizing LLM Use in Healthcare: Identifying Patient Questions in MyChart Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The volume of patient-provider messages is on the rise, and Large Language Models (LLMs) can potentially streamline the clinical messaging process, but their success hinges on triaging messages they can optimally address. In this study, we analyzed E...

Generative AI Demonstrated Difficulty Reasoning on Nursing Flowsheet Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Excessive documentation burden is linked to clinician burnout, thus motivating efforts to reduce burden. Generative artificial intelligence (AI) poses opportunities for burden reduction but requires rigorous assessment. We evaluated the ability of a ...

BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The advent of clinical language models integrated into electronic health records (EHR) for clinical decision support has marked a significant advancement, leveraging the depth of clinical notes for improved decision-making. Despite their success, the...

Optimizing Large Language Models for Discharge Prediction: Best Practices in Leveraging Electronic Health Record Audit Logs.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Electronic Health Record (EHR) audit log data are increasingly utilized for clinical tasks, from workflow modeling to predictive analyses of discharge events, adverse kidney outcomes, and hospital readmissions. These data encapsulate user-EHR interac...

Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Integrating Electronic Health Records (EHR) and the application of machine learning present opportunities for enhancing the accuracy and accessibility of data-driven diabetes prediction. In particular, developing data-driven machine learning models c...