Abstract
The Deep learning prediction technique has become more popular day by day in the medical sector, mainly in predicting anti-cancer drug synergy. However, a deep learning algorithm has not been introduced sufficiently in predicting drug development against cancer. This paper aims to research literature based on the deep learning techniques to provide predictions about the effects of drug combinations based on the developed taxonomy. The end-users can see the type of data used, feature extraction tools, prediction techniques and visual display of the synergistic drug combinations that will help them to derive a more accurate drug synergy score for smooth anti-cancer treatment.
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Gautam, U.K. et al. (2022). Deep Learning Algorithm for Predicting Drug Synergy Against Cancer: Data, Drug Feature Extraction, Prediction and View (DDPV) Taxonomy. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the ICR’22 International Conference on Innovations in Computing Research. ICR 2022. Advances in Intelligent Systems and Computing, vol 1431. Springer, Cham. https://doi.org/10.1007/978-3-031-14054-9_25
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DOI: https://doi.org/10.1007/978-3-031-14054-9_25
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