Challenges Inherent in Building an Intelligent Paradigm for Tumor Detection Using Machine Learning Algorithms

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 705)

Abstract

Machine learning is at the heart of the big data rebellion sweeping the world today. It is the science of getting the computers to learn without being explicitly programmed as most of the technological systems are in an insurrection to be operated by intelligent machines capable to make the human like verdict to automatically solve human task with perfect results. Artificial intelligence is the heart of every major technological system in the world today. This paper presents the challenges faced to develop a model to acquiesce excellent results and the different techniques of machine learning; here, we also present the broad view of the current techniques used for detection of Brain tumor in computer-aided diagnosis and an innovative method for detection of Brain tumor by artificial intelligence using the algorithm of k-nearest neighbor which is established on the training a model with different values of k and the appropriate distance metrics are used for the distance calculation between pixels.

Keywords

Machine learning Artificial intelligence Supervised learning Classification Regression Unsupervised learning K-nearest neighbor 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.GIT BelgaumBelgaumIndia
  2. 2.ADCETAshta, SangliIndia

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