To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer.
OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.
OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...
Academic medicine : journal of the Association of American Medical Colleges
Oct 1, 2019
The technology at the heart of the most innovative progress in health care artificial intelligence (AI) is in a subdomain called machine learning (ML), which describes the use of software algorithms to identify patterns in very large datasets. ML has...
Journal of the American College of Radiology : JACR
Sep 1, 2019
Recent advances in artificial intelligence (AI) are providing an opportunity to enhance existing clinical decision support (CDS) tools to improve patient safety and drive value-based imaging. We discuss the advantages and potential applications that ...
Studies in health technology and informatics
Aug 21, 2019
Many currently available Diagnostic Decision Support Systems (DDSS) are based on causal condition-symptom relations that exhibit certain shortcomings. Ada's new approach explores the capabilities of DDSS based on pathophysiology, describing a disease...
Studies in health technology and informatics
Aug 21, 2019
This paper presents a pioneering and practical experience in the development and implementation of a clinical decision support system (CDSS) based on natural language processing (NLP) and artificial intelligence (AI) techniques. Our CDSS notifies pri...
PURPOSE: We have created a cloud-based machine learning system (CLOBNET) that is an open-source, lean infrastructure for electronic health record (EHR) data integration and is capable of extract, transform, and load (ETL) processing. CLOBNET enables ...
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