Genomics at the Nexus of AI, Computer Vision, and Machine Learning

17Navigating the Genetic Tapestry Using Genetic Analysis on the SLC26A1 Gene Variants in the Detection and Understanding of Kidney Stones for Improved Global Healthcare Management

Sandeep Kumar^1*, Monali Gulhane², Nitin Rakesh², Sudhanshu Maurya², Rajni Mohana³ and Chanderdeep Tandon⁴

¹Department of CSE, Koneru Lakshmaiah Education Foundation, Vijayawada, India

²Department of CSE, Symbiosis Institute of Technology, Nagpur, Campus, Symbiosis International (Deemed University) Pune, India

³Department of CSE, Amity School of Engineering and Technology, Amity University, Punjab, India

⁴Department of CSE, Amity School of Biological Sciences, Amity University Punjab, Mohali, Punjab, India

Abstract

There is now a notable increase in the prevalence of hereditary diseases and kidney stones worldwide. Genetic illnesses, such as cystinuria, dental disease, and primary hyperoxaluria, are believed to have a widespread impact, affecting millions of people worldwide. Moreover, there has been a consistent increase in the prevalence of kidney stones over the last several decades, with certain groups having an estimated lifespan risk of up to 12%. This alarming pattern requires immediate investigation to tackle the increasing prevalence of kidney stones in persons with genetic predispositions. The research in this chapter focuses on the SLC26A1 gene, which can identify and provide insights into the molecular mechanisms behind calcium oxalate stones in the kidneys. The work explores previously ...