2Cancerous Cells Detection in Lung Organs of Human Body: IoT-Based Healthcare 4.0 Approach

Rohit Rastogi1*, D.K. Chaturvedi2, Sheelu Sagar3, Neeti Tandon4 and Mukund Rastogi5

1Department of CSE, ABES Engineering College Ghaziabad, U.P., India

2Dept. of Electrical Engineering, Dayalbagh Educational Institute, Agra, India

3Amity International Business School, Amity Univ., Noida, U.P., India

4Vikram University, Ujjain, M.P., India

5BTech CSE Third Year, Department of CSE, ABES Engineering College Ghaziabad, U.P., India

Abstract

Old age cancer was the cause of death. Forty percent of cancers are found in people over the age of 65. Lung cancer is one of these potentially deadly cancers. Young-, middle-, and old-aged patients, men who are chronic smokers or women who have never smoked are all victims of the disease. Therefore, a classification of lung cancer based on the associated risks (high risk, low risk, high risk) is required.

The study was conducted using a lung cancer classification scheme by studying micrographs and classifying them into a deep neural network using machine learning (ML) framework. Tissue microscopy images are based on the risk of using deep concealed neural networks. Neural Networks–Deep Conversion Deep Neural Networks are only used for classification (photo search) based on primary image (for example, displayed name) and similarity.

After that, scene recognition is performed on the stage. These algorithms help to recognize faces, tumors, people, road signs, ...

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