Comprehensive Medical Image Data Handling for Lung Cancer Stage Screening and Proactive Sustain using Deeplearning Techniques

Abstract

Lung cancer stage identification and proactive stage sustain is a difficult task to implement using the medical data images alone due to its complex structure and inter component relations.  The process of taking the medical images and maintaining it for further processing with sensitive care is an essential part in lung cancer analysis so that it will be properly handled by the appropriate smart techniques in order to perform the effectiveadvisory process for better medical recommendations.  Deep learning plays the appropriate smart technique approach for the medical experts for handling this sensitive lung cancer medical image data in an efficient way.  This paper presents the comprehensive medical image data handling for lung cancer stage screening and proactive sustain using deep learning techniques.This paper module focuses on the optimal selection of deep learning techniques to identify the types, stage and stage level recognitiontowards the lung cancer using medical image data sets.  The future extension of this paper focuses onautomated lung cancer data analysis model to access the lung cancer medical image data directly using opinion learning approaches.