Progression Analysis and Facial Emotion Recognition in Dementia Patients Using Machine Learning

The healthcare industry is ripe for some major changes. From chronic diseases and cancer to radiology and risk assessment, there are nearly endless opportunities to leverage technology to deploy more precise, efficient, and impactful interventions at exactly the right moment in a patient’s care. As technology advances, patients demand more from their doctors, and the volume of available data continues to increase at a staggering rate, artificial intelligence is poised to be the engine that drives improvements across the care continuum. No cure exists for dementia, but promising drugs have emerged in recent years that can help stem the condition’s progression. However, these treatments must be administered early in the course of the disease to do any good. This race against the clock has inspired me to search for ways to diagnose the condition earlier. This paper aims to elaborate on AI-produced smart application using machine learning that aims to aid dementia patients in identifying symptoms that highlight significant decline of cognitive functions so that they can be diagnosed and help the patient from further deterioration of dementia disease. There is often lack of awareness and understanding of Alzheimer’s which leads to delay in diagnosis and care. Thus, there is need to spread awareness which will help the community to know about this disease and can get checked for it instantly via model. Model designed achieves an accuracy of 84% which is at par with existing models.