Author:
Khari Suraj,Gupta Deepa,Chaudhary Alka,Bhatla Ruchika
Abstract
INTRODUCTION: Determining the possibility that an individual is affected by a tumour is an intricate process in today's modern technological and biological age, when feats are reaching unprecedented levels with every passing second. Machine learning modalities could dramatically enhance the accuracy of diagnosis.
OBJECTIVES: Our research makes it feasible to detect tumours early, aiding in early diagnosis, and is a necessity for the curative efforts of cancer patients.
METHODS: In our research model Convolutional Neural Network (CNN) was implemented using Jupiter to give an accurate result.
RESULTS: In our proposed model we got 99% accuracy that is higher than the other results.
CONCLUSION: Our research demonstrates the potential of using machine learning techniques to improve the accuracy and efficiency of medical diagnosis.
Publisher
European Alliance for Innovation n.o.
Subject
Health Informatics,Computer Science (miscellaneous)
Cited by
1 articles.
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