Online Intelligent Smart Health Prediction Using Machine Learning
Keywords:
Neural Network, Convolution, Parkinson’s, WHO, ClassifierAbstract
There are a number of single illness prediction ML initiatives that are primarily focused on prediction, making it difficult for users to use. To address this issue, we developed this sophisticated system that can forecast multiple diseases and has a user-friendly interface. During a pandemic, most people would prefer to be treated at home as much as possible to avoid polluted locations such as hospitals and clinics. The purpose of our project is to establish a user-friendly platform for cross-validating results while on the road, as well as to promote general awareness and provide preventative measures [11]. Many deaths are caused by diseases such as diabetes, lung cancer, and heart-related ailments around the world; nevertheless, the bulk of deaths occur due to a lack of regular health exams [12]. Because of a lack of medical infrastructure and a low doctor-to-population ratio, the following problem occurs. According to WHO guidelines, the doctor-to-patient ratio should be 1:1000, however India's doctor-to-population ratio is 1:1457, indicating a doctor deficit. The purpose of this research is to apply artificial intelligence (AI) to forecast serious ailments such kidney infection, diabetes, liver disease, pneumonia, Parkinson's disease, Covid-19, malaria, and cellular breakdown in the lungs. To make this work more consistent and accessible to the general public, our group designed an online application that uses AI to generate disease forecasts. The major purpose of this project is to create an online application that uses artificial intelligence to anticipate the diseases stated. There would be a significant danger to our humanity. If diseases such as heart disease, kidney disease, pneumonia, diabetes, malaria, and other maladies are not recognised and prevented at an early stage, they might lead to death. Many lives can be saved by early detection and prevention of these disorders [10]. The Random Forest Classifier and Convolution Neural Network algorithms are used in the Online Intelligent Health Care system to predict illness risk levels.
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Copyright (c) 2022 Pola Aashray, Maryala Manish, Bingi Abhishek, Mohan Dholvan
This work is licensed under a Creative Commons Attribution 4.0 International License.