Programs
- Ph. D. in Mechanical Engineering -
- B.Tech. in Artificial Intelligence (AI) and Data Science (Medical Engineering) - Undergraduate
Publication Type : Conference Paper
Thematic Areas : Learning-Technologies
Publisher : Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018, Institute of Electrical and Electronics Engineers .
Source : Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018, Institute of Electrical and Electronics Engineers Inc. (2018)
ISBN : 9781538637852
Keywords : Biological organs, Computer aided instruction, Convolution, Deep learning, Diagnosis, Diagnosis of lung cancer, Diseases, Extract informations, Forecasting, Learning environments, lung cancer, Network-based, Pathological images, pharmacogenomics, Prediction model.
Campus : Amritapuri
School : School of Engineering
Center : Technologies & Education (AmritaCREATE), Amrita Center For Research in Analytics
Department : Computer Science and Engineering
Year : 2018
Abstract : The recently introduced deep learning environment has been used in post pharmacogenomic predictions on proneness to lung cancer. The well-established pre-trained model, VGG19 has been used to extract information from the pathological images specific to PTEN, EGFR, ERBB2, BRAF and CDKN2A for Lung cancer. The model finds to be suitable for the prediction of these mutations, specific to Indian populations. A model consisting of testing of specific genetic signatures and the deep convolution network based image classification has been suggested as an ingenious technique for the fast, cheap and effective predictions on mutations of lung cancer among Indian populations. © 2018 IEEE.
Cite this Research Publication : A. Iyer, Vyshnavi, H. A. M., and Namboori, P. K., “Deep Convolution Network Based Prediction Model for Medical Diagnosis of Lung Cancer - A Deep Pharmacogenomic Approach : Deep diagnosis for lung cancer”, in Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018, 2018.