Convolutional Neural Network in Medical Diagnosis
Author(s):
Vivek Paul, Anshul Gupta
Keywords:
Convolutional Neural Network, AlexNet, ZFNet, VGGNet, GoogleNet, ResNet and Medical Diagnosis
Abstract
Convolutional Neural Network (CNN) is transforming the field of medical diagnosis. CNN can help doctors make faster, more accurate diagnosis by providing automatic learning techniques for predicting the common patterns from the medical image data. Human expert provides limited interpretation of medical images due to its subjectivity, complexity and extensive variations across the image. CNN is able to provide state of the art solutions with good accuracy for medical imaging and is powered by the increasing availability of healthcare data. Major disease areas that use CNN includes cancer, dermatology, neurology and cardiology. This paper focuses on the use of different CNN architectures based on their performance for accurate medical diagnosis. We also discuss the current status of CNN applications in healthcare and its various limitations.
Article Details
Unique Paper ID: 148231

Publication Volume & Issue: Volume 5, Issue 12

Page(s): 718 - 725
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews