AIMC Topic: United States

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Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In evolving clinical environments, the accuracy of prediction models deteriorates over time. Guidance on the design of model updating policies is limited, and there is limited exploration of the impact of different policies on future model performanc...

A High Recall Classifier for Selecting Articles for MEDLINE Indexing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
MEDLINE is the National Library of Medicine's premier bibliographic database for biomedical literature. A highly valuable feature of the database is that each record is manually indexed with a controlled vocabulary called MeSH. Most MEDLINE journals ...

Regional Variations in Documentation of Sexual Trauma Concepts in Electronic Medical Records in the United States Veterans Health Administration.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Experiences of sexual trauma are associated with adverse patient and health system outcomes, but are not systematically documented in electronic health records (EHR). To describe variations in how sexual trauma is documented in the Veterans Health ...

Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This d...

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

JAMA network open
IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.

Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

Circulation. Heart failure
BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvas...

Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records.

Translational psychiatry
Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS) for suicide attempt could prove valuable for identifying those at risk of suicide attempts, and analyzing the contribution of repeated attempts to th...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

BMJ open
INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visua...

Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

Current diabetes reports
PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications. Although various models of ML have been developed, most have not led to practical solutions for rea...