Osteoporosis Disease: The Impact of Vitamin Deficiency in Indian Population Using Machine Learning

Osteoporosis is a deficiency in bones, hormonal disorders, and insufficient calcium and vitamins; these symptoms can cause fractures. Sometimes, it may lead to cause of death. Untreated, this disease can lead to life-threatening and the maximum time people leave it within treatment. A survey was carried out on this deficiency of vitamin C and calcium in people in the region of India aged 30 to 50 years. This study has not included content like costs and any inadequacies. It’s carried out on actual, real health scenarios. Various machine learning models have been carried out, and models like regression, XGBoost, and Xgboost have been used. Xgboost has shown the best among them. This study of the model showed similar results for the random forest and XGBoost product. This result shows the complete studies of osteoporosis problems. Osteoporosis is a common health disease due to imbalances in hormonal and calcium deficiencies and lack of vitamin D. This is a critical health issue in India and affects many people. This research investigates identifying osteoporosis in vitamin C and vitamin D; this study used a secondary dataset from Kaggle’s image, producing bone X-rays to classify whether the person is affected by osteoporosis or not. Different algorithms are used to classify the data. The result produced by the algorithms shows the best accuracy among the other. Here, XGBoost produced the best accuracy compared with different algorithms. Predicting the disease in the early stage can emphasise early detection to mitigate the conditions. This research provides a complete understanding of vitamin deficiency using images and the risk of osteoporosis and proposes predictive models to enhance early diagnosis and intervention.