AI-Enhanced Blood Testing for Disease Detection and Monitoring
Year: 2024
Type: article
Abstract: This paper presents a survey of artificial intelligence (AI) applications in blood testing for disease detection and patient monitoring. It covers several machine learning (ML) models like deep neural networks (DNN), decision trees, and support vector machines (SVM) used to interpret blood test results. The integration of AI with routine blood tests promises to enhance the diagnostic accuracy, reduce costs, and also improve patient outcomes. This paper compares different AI approaches in this domain, discusses the challenges and limitations, and explores the future scope of AI in clinical settings.AI in Healthcare, Blood Test Analysis, Machine Learning, Disease Detection, Deep Learning, Clinical Diagnostics.
Authors: Soumya A.V, Archana Menon, Arathy Joshy, Devika Denson, Diya Santhosh
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W6930458645