Research Article
Use of Deep Learning in Personalized Medicine: Current Trends and the Future Perspective
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303118, author={Arooj Hussain and Sameena Naaz}, title={Use of Deep Learning in Personalized Medicine: Current Trends and the Future Perspective}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={personalized medicine deep neural network (dnn) convolutional neural network (cnn) linear regression support vector machine variational autoencoder}, doi={10.4108/eai.27-2-2020.2303118} }- Arooj Hussain
Sameena Naaz
Year: 2021
Use of Deep Learning in Personalized Medicine: Current Trends and the Future Perspective
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303118
Abstract
Personalized Medicine is about to bring a paradigm shift in the way diseases are being treated across the world today. The first step to achieve Accurate Prognosis of medication however, is to attain Accurate Diagnosis of diseases. Due to this, the primary step in the direction of Personalized Treatment is to apply various Machine Learning and Deep Learning methods to predict the diseases and drug responses from various inputs such as Magnetic Resonance Images, CT Scans, PET Scans, etc. This paper aims to canvass the research studies that have been conducted in the previous 2-3 years to employ ML and DL techniques in predicting disorders as well as predicting responses to drugs from scans, images and other similar data. The disorders included are lung cancer, breast cancer, brain tumor, diabetes etc. One technique that has repeatedly been used by the researchers and which has replicated good results generally is the Convolutional Neural Network.