Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges

Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges

Abstract Chronic diseases such as heart disease, cancer, and diabetes are leading drivers of mortality worldwide, underscoring the need for improved efforts around early detection and prediction. The pathophysiology and management of chronic diseases have benefitted from emerging fields in molecular...

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Podrobná bibliografie
Hlavní autoři: Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi
Médium: Článek
Jazyk:English
Vydáno: Wiley 2025-03-01
Edice:Chronic Diseases and Translational Medicine
Témata:
big data
chronic diseases
disease prediction
machine learning algorithms
OMICs data
On-line přístup:https://doi.org/10.1002/cdt3.137

Internet

https://doi.org/10.1002/cdt3.137

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