Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Proceedings of the National Academy of Sciences of the United States of America
Yonatan ElulYael Yaniv

Abstract

Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically meaningful terms, handling the presence of unknown medical conditions, and transparency regarding the system's limitations, both in terms of statistical performance as well as recognizing situations for which the system's predictions are irrelevant. We articulate these unmet clinical needs as machine-learning (ML) problems and systematically address them with cutting-edge ML techniques. We focus on electrocardiogram (ECG) analysis as an example domain in which AI has great potential and tackle two challenging tasks: the detection of a heterogeneous mix of known and unknown arrhythmias from ECG and the identification of underlying cardio-pathology from segments annotated as normal sinus rhythm recorded in patients with an intermittent arrhythmia. We validate our methods by simulating a screening for arrhythmias in a large-scale population while adhering to statistical significance requirements. Specifically, our system 1) visualizes the relative importance of each part of an ECG seg...Continue Reading

References

Jun 2, 2007·Europace : European Pacing, Arrhythmias, and Cardiac Electrophysiology : Journal of the Working Groups on Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology·Simona PetrutiuSteven Swiryn
Feb 10, 2010·Nature Reviews. Cardiology·A Selcuk AdabagBernard J Gersh
Dec 15, 2015·Nature Reviews. Cardiology·Liang-Han LingRoss J Hunter
Jan 5, 2016·Nature Reviews. Cardiology·Michel HaissaguerreOlivier Bernus
Jan 18, 2016·Computer Methods and Programs in Biomedicine·Eduardo José da S LuzDavid Menotti
Jan 27, 2016·Circulation·UNKNOWN Writing Group MembersUNKNOWN Stroke Statistics Subcommittee
Oct 7, 2016·Nature·Davide Castelvecchi
May 10, 2017·Circulation·Ben FreedmanUNKNOWN AF-Screen Collaborators
Oct 20, 2017·Europace : European Pacing, Arrhythmias, and Cardiac Electrophysiology : Journal of the Working Groups on Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology·Georges H MairesseUNKNOWN ESC Scientific Document Group
Apr 6, 2018·Journal of the Royal Society, Interface·Travers ChingCasey S Greene
Aug 15, 2018·Nature Medicine·Jeffrey De FauwOlaf Ronneberger
Jan 9, 2019·Nature Medicine·Andre EstevaJeff Dean
Jan 9, 2019·Nature Medicine·Beau NorgeotAtul J Butte
Apr 4, 2019·The New England Journal of Medicine·Alvin RajkomarIsaac Kohane
May 8, 2018·NPJ Digital Medicine·Alvin RajkomarJeffrey Dean
Aug 21, 2019·Nature Medicine·Jenna WiensAnna Goldenberg
Aug 28, 2019·NPJ Digital Medicine·Trishan PanchLeo Anthony Celi
Jan 3, 2020·Nature·Scott Mayer McKinneyShravya Shetty
May 13, 2020·Nature Medicine·Sushravya RaghunathBrandon K Fornwalt

❮ Previous
Next ❯

Related Concepts

Related Feeds

Atrial Fibrillation

Atrial fibrillation is a common arrhythmia that is associated with substantial morbidity and mortality, particularly due to stroke and thromboembolism. Here is the latest research.

Arrhythmia

Arrhythmias are abnormalities in heart rhythms, which can be either too fast or too slow. They can result from abnormalities of the initiation of an impulse or impulse conduction or a combination of both. Here is the latest research on arrhythmias.