• Manju Saini
• Dharmender Kumar

The Healthcare production needs more complex and sophisticated data for high end research. The conclusive statement got from the doctor or any type of suggestive things like web mining, data mining and neural network analysis always is predictive. Always there is chance to improvises the expected result through better treatment process. These processes need very huge study of patient’s data. It is quite tough to arrange huge and real data sets for present’s research. So this paper introduces neural network technique for generating the real data sets.This will facilities self-generating vales of patients’ record values. Neural network itself is capable and sufficient generator of all kind of data type. It just needs the variety of attributes and respective range and further it feed to training sets. In this article it is assuring to the patient have better interface system that have the power of judgement critical disease. This includes the appearance of NN that will enhance the make the console more decisive.This will provide the training sets to the console for making the distinguish the exaggerated region and unaffected region of body parts. Other Algorithms like A-Priori, K-Mean and PSO is also be used for creation the earlier tools in console. Web Mining will provide the key information and attributes collected through blogs, social sites and surveys.

Neural Network, Epoch, Perception, Web Mining Approach, Healthcare Production, PSO, K-Mean, A-Priori.

"ANALYSIS OF CRITICAL DISEASE IMAGES USING NEURAL NETWORK & ORL DATABASE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.336-341, May-2019, Available :http://www.jetir.org/papers/JETIR1905551.pdf

"ANALYSIS OF CRITICAL DISEASE IMAGES USING NEURAL NETWORK & ORL DATABASE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp336-341, May-2019, Available at : http://www.jetir.org/papers/JETIR1905551.pdf