Paper Details
A REVIEW OF LUNG CANCER ANALYSIS USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING ALGORITHMS
Authors
B.Durgalakshmi, M.Deepika
Abstract
Lung cancer is a fatal disease with a high mortality rate in diseased patients. Early diagnosis of this disease and accurately identifying the lung cancer stage can save the patients’ lives. Several image processing, based and machine automation approaches are used to identify lung cancer, but accuracy and early diagnosis are challenging for medical practitioners. The Lung Image Database Consortium and Image Database Resource Initiatives are utilized in this study to extract the CT scan images. In conventional methods, manual CT images are supplied to visualize whether the person has lung cancer. This research article proposes a novel method for early and accurate diagnosis called cancer cell detection using hybrid neural networks and other algorithms.The features are extracted from the CT scan images using deep neural networks. The accuracy of feature extraction is very important to detect cancerous cells at early stages to save the patient from this fatal disease.
Keywords
Neural Networks,Deep Learning
Citation
A REVIEW OF LUNG CANCER ANALYSIS USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING ALGORITHMS. B.Durgalakshmi, M.Deepika. 2024. IJIRCT, Volume 10, Issue 4. Pages 1-13. https://www.ijirct.org/viewPaper.php?paperId=2408052