Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/7064
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dc.contributor.authorShankar, M.-
dc.contributor.authorPahadia, M.-
dc.contributor.authorSrivastava, D.-
dc.contributor.authorAshwin, T.S.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.date.accessioned2020-03-30T09:58:28Z-
dc.date.available2020-03-30T09:58:28Z-
dc.date.issued2015-
dc.identifier.citationProceedings - 2015 2nd IEEE International Conference on Advances in Computing and Communication Engineering, ICACCE 2015, 2015, Vol., , pp.679-682en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/7064-
dc.description.abstractHealthcare is a sector where decisions usually have very high-risk and high-cost associated with them. One bad choice can cost a person's life. With diseases like Swine Flu on the rise, which have symptoms quite similar to common cold, it's very difficult for people to differentiate between medical conditions. We propose a novel method for recognition of diseases and prediction of their cure time based on the symptoms. We do this by assigning different coefficients to each symptom of a disease, and filtering the dataset with the severity score assigned to each symptom by the user. The diseases are identified based on a numerical value calculated in the fashion mentioned above. For predicting the cure time of a disease, we use reinforcement learning. Our algorithm takes into account the similarity between the condition of the current user and other users who have suffered from the same disease, and uses the similarity scores as weights in prediction of cure time. We also predict the current medical condition of user relative to people who have suffered from same disease. � 2015 IEEE.en_US
dc.titleA Novel Method for Disease Recognition and Cure Time Prediction Based on Symptomsen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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