Аннотация:In this study, machine learning methods are used to forecast sickness symptoms.Correct and timely evaluation of health-related problems is essential to disease prevention and treatment that is effective.Machine learning algorithms offer a potential approach for detecting the onset of diseases by looking at a variety of symptoms and medical records.In this case, it is suggested to use the Never-Ending Image Learner (NEIL) for automatic online forecasting of typical sickness indicators.An ontology-based prediction method for typical sickness features is also presented in this paper.The Deep Electronic Health Record (EHR) system is also displayed.This system uses both structured and unstructured data to predict when an illness may start.The use of machine learning techniques to predict diseases like Covid-19 may result in decreased disease transmission rates and quicker disease detection, it is vital to mention.The study also investigates the development of a system that employs machine learning to distinguish various human skin states and intelligently predict skin illnesses.The research also looks into how data mining and machine learning may be used to diagnose and forecast heart illness.By enabling quick and precise diagnoses that eventually result in better patient outcomes, the use of machine learning algorithms to predict illness symptoms has the potential to change the healthcare industry.
