AIMC Topic: Antineoplastic Agents
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Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.
Briefings in bioinformatics
Jul 25, 2024
With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent scientific and societal issues. To this end, the European Union passed the EU AI Act, proposing solu...
Predicting drug synergy using a network propagation inspired machine learning framework.
Briefings in functional genomics
Jul 19, 2024
Combination therapy is a promising strategy for cancers, increasing therapeutic options and reducing drug resistance. Yet, systematic identification of efficacious drug combinations is limited by the combinatorial explosion caused by a large number o...
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Deep learning models are being adopted and applied across various critical medical tasks, yet they are primarily trained to provide point predictions without providing degrees of confidence. Medical practitioner's trustworthiness of deep learning mod...
CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations.
Bioinformatics (Oxford, England)
Jun 28, 2024
MOTIVATION: High-throughput screens (HTS) provide a powerful tool to decipher the causal effects of chemical and genetic perturbations on cancer cell lines. Their ability to evaluate a wide spectrum of interventions, from single drugs to intricate dr...
Focus on emerging cancer drugs, artificial intelligence applied to imaging, and a new therapeutic target in heart failure.
European heart journal
Jun 7, 2024
How Artificial Intelligence Unravels the Complex Web of Cancer Drug Response.
Cancer research
Jun 4, 2024
The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cel...
Integration of autoencoder and graph convolutional network for predicting breast cancer drug response.
Journal of bioinformatics and computational biology
Jun 1, 2024
Breast cancer is the most prevalent type of cancer among women. The effectiveness of anticancer pharmacological therapy may get adversely affected by tumor heterogeneity that includes genetic and transcriptomic features. This leads to clinical varia...
Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking.
Drug development research
Jun 1, 2024
Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk model of BC and identify prognostic biomarkers through machine learning approaches, and clarify the mechanism by which linalool exerts tumor-suppressive f...
Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data.
Briefings in bioinformatics
May 23, 2024
The inherent heterogeneity of cancer contributes to highly variable responses to any anticancer treatments. This underscores the need to first identify precise biomarkers through complex multi-omics datasets that are now available. Although much rese...
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction.
Briefings in bioinformatics
May 23, 2024
A major challenge of precision oncology is the identification and prioritization of suitable treatment options based on molecular biomarkers of the considered tumor. In pursuit of this goal, large cancer cell line panels have successfully been studie...
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