Predicting acute myocardial infarction from haematological markers utilizing machine learning and explainable artificial intelligence

Predicting acute myocardial infarction from haematological markers utilizing machine learning and explainable artificial intelligence

Myocardial infarction (MI) is the leading cause of human death globally. It occurs when a blockage in an artery prevents blood and oxygen from reaching the heart muscle, causing tissues in the heart muscle to die. This leads to a necessity to develop a method to diagnose MI’s early, preventing furth...

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Bibliographic Details
Main Authors: Tejas Kadengodlu Bhat, Krishnaraj Chadaga, Niranjana Sampathila, Swathi KS, Rajagopala Chadaga, Shashikiran Umakanth, Srikanth Prabhu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Systems Science & Control Engineering
Subjects:
Myocardial infarction
machine learning
explainable artificial intelligence
hematological parameters
Online Access:https://www.tandfonline.com/doi/10.1080/21642583.2024.2331074

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