The Drug Response Prediction for Cancer Patients' Personalized Treatment by Deep Learning on Omics Features

• Published in: 2023 IEEE Smart World Congress (SWC) pp. 1 - 8
• Main Authors: Yao, Zeyu, Liu, Ruhao, Zhang, Qingchen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.08.2023
• Subjects: cancer patients' personalized treatment; deep learning; drug response prediction; omics features
• DOI: 10.1109/SWC57546.2023.10448992

Predicting the response of tumors to cancer treatment drugs is currently an important challenge for personalized cancer treatment. In recent years, deep learning has been widely applied in the field of drug reaction prediction. Most of existing research for drug response are based on cancer patients' omics features. This article summarizes the research on the application of deep learning(DL) method to predict drug reactions in cancer cell lines. We provide a brief overview of the multiple sets of data currently used for drug reaction prediction, as well as an introduction to the publicly available datasets used in current research experiments. Then, we will provide a detailed introduction to some models and methods for predicting drug reactions based on deep learning. Finally, we provide suggestions for future work in response to the problems in our research methods.