Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study

Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study

(1) Background: Cardiac amyloidosis (CA) is a rare and complex condition with poor prognosis. While novel therapies improve outcomes, many affected individuals remain undiagnosed due to a lack of awareness among clinicians. This study was undertaken to develop an expert-independent machine learning...

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Bibliographic Details
Main Authors: Asan Agibetov, Benjamin Seirer, Theresa-Marie Dachs, Matthias Koschutnik, Daniel Dalos, René Rettl, Franz Duca, Lore Schrutka, Hermine Agis, Renate Kain, Michela Auer-Grumbach, Christina Binder, Julia Mascherbauer, Christian Hengstenberg, Matthias Samwald, Georg Dorffner, Diana Bonderman
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Journal of Clinical Medicine
Subjects:
heart failure
cardiac amyloidosis
machine learning
artificial intelligence
Online Access:https://www.mdpi.com/2077-0383/9/5/1334

Internet

https://www.mdpi.com/2077-0383/9/5/1334

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