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

Showing 101 to 110 of 377 articles

Towards User-centered Corpus Development: Lessons Learnt from Designing and Developing MedTator.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A gold standard annotated corpus is usually indispensable when developing natural language processing (NLP) systems. Building a high-quality annotated corpus for clinical NLP requires considerable time and domain expertise during the annotation proce...

A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, failure to adjust for SBDoH factors will potentially cause confounding i...

Integrating Multimodal Electronic Health Records for Diagnosis Prediction.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Diagnosis prediction aims to predict the patient's future diagnosis based on their Electronic Health Records (EHRs). Most existing works adopt recurrent neural networks (RNNs) to model the sequential EHR data. However, they mainly utilize medical cod...

A Machine Learning Pipeline for Accurate COVID-19 Health Outcome Prediction using Longitudinal Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Current COVID-19 predictive models primarily focus on predicting the risk of mortality, and rely on COVID-19 specific medical data such as chest imaging after COVID-19 diagnosis. In this project, we developed an innovative supervised machine learning...

Learning Predictive and Interpretable Timeseries Summaries from ICU Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Machine learning models that utilize patient data across time (rather than just the most recent measurements) have increased performance for many risk stratification tasks in the intensive care unit. However, many of these models and their learned re...

First-line drug resistance profiling of : a machine learning approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The persistence and emergence of new multi-drug resistant Mycobacterium tuberculosis (M. tb) strains continues to advance the devastating tuberculosis (TB) epidemic. Robust systems are needed to accurately and rapidly perform drug-resistance profilin...

Automated Mapping of Real-world Oncology Laboratory Data to LOINC.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In this study we seek to determine the efficacy of using automated mapping methods to reduce the manual mapping burden of laboratory data to LOINC(r) on a nationwide electronic health record derived oncology specific dataset. We developed novel encod...

Data and Model Biases in Social Media Analyses: A Case Study of COVID-19 Tweets.

AMIA ... Annual Symposium proceedings. AMIA Symposium
During the coronavirus disease pandemic (COVID-19), social media platforms such as Twitter have become a venue for individuals, health professionals, and government agencies to share COVID-19 information. Twitter has been a popular source of data for...

Predicting Motor Responsiveness to Deep Brain Stimulation with Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Deep brain stimulation is a complex movement disorder intervention that requires highly invasive brain surgery. Clinicians struggle to predict how patients will respond to this treatment. To address this problem, we are working toward developing a cl...

Impact of Clinical and Genomic Factors on COVID-19 Disease Severity.

AMIA ... Annual Symposium proceedings. AMIA Symposium
To date, there have been 180 million confirmed cases of COVID-19, with more than 3.8 million deaths, reported to WHO worldwide. In this paper we address the problem of understanding the host genome's influence, in concert with clinical variables, on ...