Back to search

Article

Artificial Intelligence-Enabled, Fully Automated Detection of Cardiac Amyloidosis Using Electrocardiograms and Echocardiograms

2020-07-05

Abstract excerpt

Although individually uncommon, rare diseases collectively affect over 350 million patients worldwide and are increasingly the target of therapeutic development efforts 1 . Unfortunately, the pursuit and use of such therapies have been hindered by a common challenge: patients with specific rare diseases are difficult to identify, especially if the conditions resemble more prevalent disorders. Cardiac amyloidosis i...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
87fa601a-72cd-54ba-8aa6-85bb91a3d0d2
DOI
10.1101/2020.07.02.20141028
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Artificial Intelligence-Enabled, Fully Automated Detection of Cardiac Amyloidosis Using Electrocardiograms and EchocardiogramsDOI 10.1101/2020.07.02.20141028
Artificial Intelligence in Cardiac Amyloidosis: A State-of-the-Art ReviewSemantic proximity
Tracking the Preclinical Progression of Transthyretin Amyloid Cardiomyopathy Using Artificial Intelligence-Enabled Electrocardiography and EchocardiographySemantic proximity
Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center studySemantic proximity
Screening for patients at risk for cardiac amyloidosis via electronic health records: A multicenter machine learning development and validation studySemantic proximity
Impact of Case and Control Selection on Training AI Screening of Cardiac AmyloidosisSemantic proximity
A Proof-of-Concept Multimodal Framework for Transthyretin Amyloidosis Classification from Clinical Narratives and ECG ImagesSemantic proximity
Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk PredictionSemantic proximity
Composite Artificial Intelligence–Enabled Electrocardiogram for Detection and Prediction of Structural Heart DiseaseSemantic proximity
Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.Semantic proximity
An Artificial Intelligence Model for Detection of Heart Failure with Preserved Ejection Fraction: A Report from HeartShare StudySemantic proximity
Integrating multimodal intelligence in heart failure: AI-driven risk prediction, precision diagnosis, phenotyping, personalized treatment, and prognosis.Semantic proximity
Multimodal Artificial Intelligence Approaches for the Diagnosis and Understanding of Heart Failure: A Contemporary ReviewSemantic proximity
Select a neighboring publication to make it the new centre.