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

Showing 21 to 30 of 377 articles

Combining Rule-based NLP-lite with Rapid Iterative Chart Adjudication for Creation of a Large, Accurately Curated Cohort from EHR data: A Case Study in the Context of a Clinical Trial Emulation.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The aim of this work was to create a gold-standard curated cohort of 10,000+ cases from the Veteran Affairs (VA) corporate data warehouse (CDW) for virtual emulation of a randomized clinical trial (CSP#592). The trial had six inclusion/exclusion crit...

RealMedQA: A pilot biomedical question answering dataset containing realistic clinical questions.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clinical question answering systems have the potential to provide clinicians with relevant and timely answers to their questions. Nonetheless, despite the advances that have been made, adoption of these systems in clinical settings has been slow. One...

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team...

Enhancing Semantic and Structure Modeling of Diseases for Diagnosis Prediction.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Electronic Health Records (EHRs) are valuable healthcare data, aiding researchers and doctors in improving diagnosis accuracy. Researchers have developed several predictive models by learning disease representations to forecast the potential diagnosi...

Robust Visual Identification of Under-resourced Dermatological Diagnoses with Classifier-Steered Background Masking.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Collecting images of rare dermatological diseases for machine learning detection applications is a costly, laborious task. It is difficult to collect enough images of these diagnoses to avoid the risk of low accuracy "in the wild". One of the sources...

Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk of heart failure (HF) is critical to improving cancer treatment outcomes and safety. This study examined mach...

Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

AMIA ... Annual Symposium proceedings. AMIA Symposium
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) models in a retrospective cohort study with a large sample size. We analyzed the association between depr...

Does Cohort Selection Affect Machine Learning from Clinical Data?

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study investigates cohort selection and its effects on the quality of machine learning (ML) models trained on clinical data, focusing on measurements taken within the first 48 hours of hospital admission. It discusses the potential repercussions...

Meta-Learning on Augmented Gene Expression Profiles for Enhanced Lung Cancer Detection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Gene expression profiles obtained through DNA microarray have proven successful in providing critical information for cancer detection classifiers. However, the limited number of samples in these datasets poses a challenge to employ complex methodolo...