Early-Stage Disease Prediction from Various Symptoms Using Machine Learning Models





Data analytics, healthcare, disease, prediction, machine learning


Development and exploration of several Data analytics techniques in various real-time applications (e.g., Industry, Healthcare Neuroscience) in various domains have led to exploitation of it to extract paramount features from datasets. Following the introduction of new computer technology, the health sector had a significant transformation that compelled it to produce more medical data, which gave rise to a number of new disciplines of study. Quite a few initiatives are made to deal with the medical data and how its usage can be helpful to humans. This inspired academics and other institutions to use techniques like data analytics, its types, machine learning and different algorithms, to extract practical information and aid in decision-making. The healthcare data can be used to develop a health prediction system that can improve a person's health. Based on the dataset provided, making accurate predictions in early disease prediction benefits the human community.


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How to Cite

D. Ajmera, T. N. Pandey, S. Singh, S. Pal, S. Vyas, and C. K. Nayak, “Early-Stage Disease Prediction from Various Symptoms Using Machine Learning Models”, EAI Endorsed Trans IoT, vol. 10, Mar. 2024.