An Integrated Machine Learning Architecture for Multi-Disease Prediction Using Ensemble Models and Advanced Training-Optimization Techniques

One of the key ones is the early diagnosis of diseases. is an issue of modern healthcare, particularly in patients. get a number of health complications simultaneously. Existing Machine learning-based disease prediction. specializes on individual disorders, and this reduces their efficiency. to offer comprehensive diagnostic help. This paper presents a prediction web platform is an integrated prediction of multiple diseases. four common illnesses within the system has machine learning algorithms that are trained on clinical and demographic data, such as age, glucose levels, and so on, blood pressure, body mass index and lifestyle choices. Each Disease module is developed by the use of preprocessing techniques. as data normalization and feature selection in order to enhance predictive accuracy. Integrating dissimilar disease models. user interface, a user can just enter in his or her health information. when considered independently and are collectively foreseen to each circumstance, Hence making it more efficient, accessible and the user in general.