Predictive Algorithms Based On Machine Learning For Infectious Disease Outbreaks And Spread

Author(s)	Prof.Mrs Tejaswini Abhishek Puranik
Country	India
Abstract	The study aims to demonstrate whether machine learning can be used to predict infectious disease outbreaks early. The Cochrane Collaboration's guidelines, the meta-analysis of observational studies in epidemiology, and the preferred reporting items for systematic reviews and meta-analyses were followed in this study. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.
Keywords	Machine Learning epidemiology PubMed infectious diseases
Field	Engineering
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-07-09
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.50647
Short DOI	https://doi.org/g9s9kw

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research