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Genetic Screening and Soft Computing Algorithms for Risk Prediction

Genetic Screening and Soft Computing Algorithms for Risk Prediction
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Author(s): Surekha Janrao (K.J. Somaiya Institute of Technology, India), Madhura Phadke (K.J. Somaiya Institute of Technology, India), Reshma Koli (A.P. Shah Institute of Technology, India)and Jayesh Sarwade (JSPM's Rajarshi Shahu College of Engineering, Pune, India)
Copyright: 2024
Pages: 30
Source title: Modernizing Maternal Care With Digital Technologies
Source Author(s)/Editor(s): Dattatray Takale (Vishwakarma Institute of Information Technology, India), Parikshit Mahalle (Vishwakarma Institute of Information Technology, India), Meera Narvekar (University of Mumbai, India)and Rupali Mahajan (Vishwakarma Institute of Information Technology, India)
DOI: 10.4018/979-8-3693-3711-0.ch005

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Abstract

Genetic screening, along with improvements in soft computing methods, is a powerful way to figure out a person's risk factors for getting different diseases and conditions. The idea in this study is to use genetic screening methods and soft computing algorithms together in a structure that makes risk forecast more accurate. Genetic screening lets doctors find specific genetic markers and differences that are linked to a higher risk of getting diseases. By looking at a person's genes, possible risk factors can be found early on, which lets people take proactive steps to reduce or control these risks successfully. However, it is very hard to find useful trends and relationships in genetic data because it is so big and complicated. Soft computing methods are a hopeful way to deal with these problems because they provide adaptable and flexible computing tools that can handle the uncertainty and missing information that come with genetic data.

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