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Cases of LDs (Lung Diseases) are increasing rapidly. In most disease that affects humans LDs have proven to be fatal in many cases including the current wave of Corona. More than one lakh Indians are affected perennially as LDs have a propensity to remain asymptomatic, especially in the early stages, making detection practically impossible. As a result, early detection of LDs can play a crucial role in saving lives since they provide patients higher chances of treatments where technologies can play critical roles. Based on these findings, several researchers have offered various ways of using CADs (Computer Aided Diagnostics) where MLTs (Machine Learning Techniques) including DLTs (Deep Learning Techniques) have been used. Furthermore, numerous approaches based on IPTs (Image Processing Techniques) have also predicted malignancy levels of lungs. Hence, this paper aims to detect LDs using DLTs. Experimental results of the proposed approach were found to be above ninety percent in terms of accuracy of detections.