MEDBOT: A MEDICAL CHATBOT FOR DISEASE DETECTION AND SUGGESTION THROUGH MACHINE LEARNING MODELS
Author(s):
Avina Wakchaure, Shamli Kavle, Shruti Surve, Apurva Patil
Keywords:
K nearest Neighbors, Linear Regression, Artificial Neural Networks and Decision Tree
Abstract
The Healthcare sector is one of the fastest growing and highly competitive sector that has been improving with the insertion of technology into this paradigm. The healthcare sector has been facing a severe lack of medical professionals that has been evident in the recent pandemic. The recent pandemic exposed the dearth of doctors and other staff in the hospitals and clinics. This is a problematic issue that will require a lot of effective improvements but the lack of the professionals has been an issue that has lasting consequences right away. The doctors that are consulting are overburdened with the patients and the elderly individuals have a hard time travelling to the hospital every time for a consultation. Therefore, the paradigm of remote diagnosis comes to the rescue. For this purpose, an effective approach called MedBot is proposed in this research article that utilizes K Nearest Neighbor clustering and Linear Regression along with Artificial Neural Networks and Decision Making. The approach has been effectively evaluated for its disease prediction and has resulted in extremely satisfactory results.
Article Details
Unique Paper ID: 156910

Publication Volume & Issue: Volume 9, Issue 5

Page(s): 397 - 403
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