• Kamal Chakravarthy Rachakonda
• Sai Charan Reddy
• P. Ashritha
• V. Swathi

In this study, we investigate the field of fall risk prediction in the senior population using advanced machine learning methods, primarily concentrating on the Logistic Regression algorithm. Our research, "Machine Learning Techniques Applied to the Development of a Fall Risk Index for Older Adults," aims to address the important problem of falls, which are a significant factor in older reliance and a major cause of unintentional trauma-related mortality. Our investigation revolves upon the Logistic Regression approach because of its interpretability and effectiveness in binary classification problems. Our goal is to utilize our large dataset to train the model in order to forecast and categorize older persons into two groups: those who fall and those who do not. The algorithm's performance metrics are rigorously evaluated, encompassing accuracy, sensitivity, and specificity in predicting fall risk. Our results demonstrate the remarkable sensitivity and specificity of Logistic Regression in effectively predicting fall risk in older persons. This study is a critical first step toward developing a customized fall prevention strategy by creating a more detailed Fall Risk Index. Beyond its immediate ramifications, this research opens the door for further projects, with the goal of creating a dynamic and all-inclusive Fall Risk Index. The main goal is to aid in the creation of proactive monitoring systems that will improve older individual’s quality of life by empowering medical practitioners to make well-informed decisions and carry out focused interventions.

Fallriskassessment, applications of machine learning, Risk index development, Predictive modeling, Logistic regression and Decision tree.

"MACHINE LEARNING TECHNIQUES APPLIED TO THE DEVELOPMENT OF A FALL RISK INDEX FOR OLDER ADULTS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.l198-l202, April-2024, Available :http://www.jetir.org/papers/JETIR2404B25.pdf

"MACHINE LEARNING TECHNIQUES APPLIED TO THE DEVELOPMENT OF A FALL RISK INDEX FOR OLDER ADULTS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppl198-l202, April-2024, Available at : http://www.jetir.org/papers/JETIR2404B25.pdf