EYECARE: SMART MOBILE EYES DISEASES EARLY DETECTION

Abstract

Cataracts are the disease that causes most eye problems and blindness in individuals, cataracts cause 30% of blindness in individuals aged 50 years and over. National data from Indonesia's Ministry of Health's 2014–2016 Rapid Assessment of Avoidable Blindness (RAAB) Blindness Survey targeting individuals aged 50 and above reveals a 3% blindness rate, with cataracts accounting for 81% of cases. Treating 81.2% of cataract cases can significantly reduce the prevalence of visual impairment in Indonesia. The Ministry of Health plays an important role in implementing advanced technologies, expert systems, and targeted interventions to improve early detection, treatment, and overall eye health of the population. The traditional cataract examination approach causes its challenges. Such as the lack of proper infrastructure and healthcare access in underdeveloped areas across the country. Disease screening methods are a crucial aspect of modern healthcare. This approach can help people, especially the elderly who are having a hard time going to the hospital and become more aware of the eye’s health. The disease screening that we propose is a mobile-based application that utilizes machine learning as an automation for diagnosing cataracts using each user's pupil’s image.