Paper Title
Lung Cancer Detection Using Deep Transfer Learning
Abstract
Abstract - One of the cancers that claims the most lives globally is lung cancer. For a patient to recover, early detection and
treatment are essential. Histopathological pictures of biopsied tissue from potentially diseased regions of the lungs are used
by medical practitioners to make diagnoses. On the other hand, pathologists are overworked, which affects how much time
they spend with each patient, how quickly they can make a diagnosis, and how much it costs to complete a case. In this
research, we design, implement, and evaluate an ANN algorithm-based diagnostic valuable resource device for non-small
cell lung cancer detection. A report module built using Deep Learning methods is included and provides the pathologist with
details on the parts of the image that were utilized to categorise the sample and the degree of confidence in each class.
Keywords - Deep Learning, ANN Algorithm, Histopathological Pictures