Prediction of the disease controllability in a complex network using machine learning algorithms

Abstract excerpt

<title>Abstract</title> <p>The application of machine learning (ML) techniques span a vast spectrum ranging from speech, face and character recognition, medical diagnosis, anomaly detection in data to the general classification, prediction and regression problems. In the present work, we solve the problem of predicting R0 for disease spreading on complex networks using the regression-based state-of-art ML techniq...

Topics

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• Bacillus and Francisella bacterial research
• Drug Design
• Drug Evaluation, Preclinical
• Liver
• Mathematical and Theoretical Epidemiology and Ecology Models
• Poxvirus research and outbreaks
• Viral Infections and Outbreaks Research
• Virology and Viral Diseases

Identifiers and source

Literature Corpus work

efc46ba2-0ae0-5eef-bbbb-4222f11063a4

DOI

10.21203/rs.3.rs-424123/v1