Obesity Related Disease Prediction from Healthcare Communities Using Machine Learning

In addition to the rapid growth of Machine Learning in biomedical and healthcare communities, the accurate analysis of medical data benefits early disease detection, patient care and community services. However, the analyses accuracy of a disease is reduced when the intake and the quality of medical data is unexplored and incomplete. Obesity happens to be a highly ignored yet a grave health issue that gives rise to a lot of potentially harmful cardiovascular diseases which if neglected could prove fatal. Many people overlook this condition not realizing that by taking small steps to improve their health they can keep many other diseases at bay. Moreover, the underlying problem that persists is not only identifying obesity as a physical medical problem but also speculating the different factors that give rise to it. The key to combatting this real-life problem and staying in the pink of health would be to thoroughly investigate and survey the many reasons as to why people get obese in the first place and eventually nip all the other probable deadly diseases in the bud because prevention is better than cure! This work aims to overcome the above-mentioned limitations by developing a state-of-the-art system that streamlines machine learning algorithms for the effective prediction of Obesity and its related diseases considering the population of India. The government indulgent regulation on food restriction provides easy accessibility to unhealthy, processed food. Also, India's growing career-oriented lifestyle gives rise to irregular biological patterns especially in younger generation who prefer indoor games rather than playing outside. The behavioral and socio-psychological factors such as sleep, stress, ethnicity in addition to hormonal disorders are influential in giving rise to obesity in today's era. There felt a need to develop a system that consider parameters affecting an individual physically, internally, mentally, psychologically and emotionally that contribute to the occurrence of Obesity and also suggest healthier alternatives to curb this problem. Some of the common diseases due to Obesity included in the system are Diabetes, Heart Attack, Hypertension, Osteoarthritis and Varicose Veins. The developed system will undeniably be beneficial for predicting obesity, its related diseases and for the future betterment of an individual.