• Tejas Shelar
• Manoj Shelar
• Shubham Dhamdhere
• Prashant Mhaske
• Prof. Anjali Almale

The health care environment is found to be rich in information, but poor in extracting knowledge from the information. This is because of the lack of effective analysis tool to discover hidden relationships and trends in them. By applying the machine learning algorithms and techniques, valuable knowledge can be extracted from the health care system. Malaria and Dengue have group of condition affecting the structure and functions of body and has many root causes. We are using Deep Learning algorithms to increase the accuracy of Malaria and Dengue Disease prediction System. We also expand this system to analysis the particular area to maximum patient will health is weak based on hospital patient data with the help of clustering. It is implemented as desktop application in which user submits the heterogeneous data like text and image of blood cells symptoms. It retrieves hidden data from stored database and deep learning model and compares the user values with trained data set.

Machine learning, Disease prediction, Area detection, Malaria, Dengue

"Viral Disease Prediction and Infected Area Detection using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 9, page no.1287-1290, September-2020, Available :http://www.jetir.org/papers/JETIR2009176.pdf

"Viral Disease Prediction and Infected Area Detection using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 9, page no. pp1287-1290, September-2020, Available at : http://www.jetir.org/papers/JETIR2009176.pdf