Machine learning approaches to drug response prediction: challenges and recent progress
Cancer is a leading cause of death worldwide. Identifying the best treatment using
computational models to personalize drug response prediction holds great promise to …
computational models to personalize drug response prediction holds great promise to …
Machine learning towards intelligent systems: applications, challenges, and opportunities
The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …
resulted in the generation of large amounts of data that can be made available for analyses …
Deep learning identifies synergistic drug combinations for treating COVID-19
Effective treatments for COVID-19 are urgently needed. However, discovering single-agent
therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV …
therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV …
[HTML][HTML] A deep learning framework for predicting response to therapy in cancer
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on
a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we …
a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we …
Deep learning for drug response prediction in cancer
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
Deep learning methods for drug response prediction in cancer: predominant and emerging trends
Cancer claims millions of lives yearly worldwide. While many therapies have been made
available in recent years, by in large cancer remains unsolved. Exploiting computational …
available in recent years, by in large cancer remains unsolved. Exploiting computational …
[HTML][HTML] Machine learning in the prediction of cancer therapy
Resistance to therapy remains a major cause of cancer treatment failures, resulting in many
cancer-related deaths. Resistance can occur at any time during the treatment, even at the …
cancer-related deaths. Resistance can occur at any time during the treatment, even at the …
Artificial intelligence in early drug discovery enabling precision medicine
Introduction: Precision medicine is the concept of treating diseases based on environmental
factors, lifestyles, and molecular profiles of patients. This approach has been found to …
factors, lifestyles, and molecular profiles of patients. This approach has been found to …
Predicting synergism of cancer drug combinations using NCI-ALMANAC data
P Sidorov, S Naulaerts, J Ariey-Bonnet… - Frontiers in …, 2019 - frontiersin.org
Drug combinations are of great interest for cancer treatment. Unfortunately, the discovery of
synergistic combinations by purely experimental means is only feasible on small sets of …
synergistic combinations by purely experimental means is only feasible on small sets of …
MatchMaker: a deep learning framework for drug synergy prediction
Drug combination therapies have been a viable strategy for the treatment of complex
diseases such as cancer due to increased efficacy and reduced side effects. However …
diseases such as cancer due to increased efficacy and reduced side effects. However …