The Potential of “GENIUS”: Deep Learning Integrated Application to Fight Obesity - Rahadi, Putu Nindya Krisnadewi; Raharja, Ananda Eka; Haidir, Andi Ahmad (IJNMT (International Journal of New Media Technology), 2024)
Lifestyle changes regarding food consumption and sedentary lifestyle has led to increase prevalence of obesity worldwide, including in Indonesia. Obesity as a risk factor for various diseases has become an urgent issue considering that currently available therapies have not shown optimal results in overcoming this problem. The "GENIUS" application is present as a body types analysis system and program recommendations for obesity therapy. The purpose of writing this paper is to find out the potential, construction mechanism, and operating mechanism of the application. The methodology of writing this paper is literature review, based on secondary data from databases such as Google Scholar, PubMed, and ScienceDirect. The construction mechanism of the application includes process of collecting dataset, creating the application and deep learning system, and launching the application. The technology utilized in the application involves image processing deep learning and recurrent neural networks, enabling it to generate outputs suit to each individual's needs and provide appropriate program recommendations. Through the "GENIUS" application, users can also consult with medical professionals, receive recommendations, and record clinical data progress in a single digital application accessible via smartphones. The application also provides an interesting sub-feature in the form of reward points given to users for using the application's features. The implementation of the application involves the quadruple helix model. The benefits of the application encompass the fields of health and knowledge, aiming to prevent obesity in order to foster an intelligent generation and achieve a healthy Indonesia.