This Study Is An Attempt To Understand And Address The Cancer Disease Prediction ,—Since, Cancer Is Curable When Diagnosed At An Early Stage, Lung Cancer Screening Plays An Important Role In Preventive Care. Although Both Low Dose Computed Tomography (LDCT) And Computed Tomography (CT) Scans Provide Greater Medical Information Than Normal Chest X-rays, Access To These Technologies In Rural Areas Is Very Limited. There Is A Recent Trend Toward Using Computer-aided Diagnosis (CADx) To Assist In The Screening And Diagnosis Of Cancer From Biomedical Images. In This Study, The 121-layer Convolutional Neural Networkalong With The Transfer Learning Scheme Is Explored As A Means Of Classifying Lung Cancer Using Chest Xray Images. The Model Was Trained On A Lung Nodule Dataset Before Training On The Lung Cancer Dataset To Alleviate The Problem Of Using A Small Dataset. The Proposed Model Yields 74.43±6.01% Of Mean Accuracy, 74.96±9.85% Of Mean Specificity, And 74.68±15.33% Of Mean Sensitivity. The Proposed Model Also Provides A Heatmap For Identifying The Location Of The Lung Nodule. These Findings Are Promising For Further Development Of Chest X-ray-based Lung Cancer Diagnosis Using The Deep Learning Approach. Moreover, They Solve The Problem Of A Small Dataset..
