Smart Healthcare System to Predict Aliments Based on Preliminary Symptoms
Publication: Springer Lecture Notes in Networks and System series, 2022
Abstract:
With the advancement of technology, there have been a plethora of breakthroughs in the healthcare sector. As a result of this, smart healthcare has progressively come into focus. In this paper, we have proposed and implemented a system that aids in the prediction and diagnosis of four medical ailments. The purpose of the proposed system is to make technology more useful in solving problematic healthcare challenges. By using this technology, we can interpret data which is obtained by diagnosing various symptoms, analyzing data, and then predicting the ailment. Through this system, we aspire to enhance public health by providing a system in their pocket that can diagnose ailments. The current lifestyle of humans has seen a drastic change over the past few years. Eating habits and the evolution of technology have played a major role in the same. Keeping this in mind, we have chosen Myopia, Colour Blindness, Polycystic Ovarian Disease (PCOD), and Probability of Heart Attack to implement in our system. We employ the power of Machine Learning to predict the probability of Heart Attack, PCOD, and Myopia. A comprehensive introduction and literature work on the prediction of these ailments, along with the methods used to predict them, are presented in this paper. Furthermore, we have discussed the results that prove the robustness and reliability of our system.