The Future of Machine Learning in Predicting the Treatment Responses of Cancers

Dear Colleagues,

After decades of research, machine learning (ML), understood as a toolbox for data analysis in medical applications, is now widely recognized as useful but only scantly applied in real medical practice. Oncology is, arguably, one of the pioneering domains in medicine in the research and development of ML-based analytical strategies. This can be at least partially explained by the many successes achieved in the analysis of medical image. A cancer-related problem that still requires much research from this point of view is the prediction of treatment responses. This includes the investigation of responses to new and experimental drugs and often involves pre-clinical studies.

This Special Issue welcomes innovative research on the use of artificial intelligence (AI) in general and ML in particular (including deep learning) for the analysis of any type of data related to the general problem of the prediction of treatment responses in cancers. This would include studies in, amongst others, clinical and pre-clinical settings and pharmacology. Contributions on personalized medicine, explainable AI, multi-modal data analysis, or data visualization, applied to or involving treatment response measures such as progression-free survival, amongst other topics, are welcome.

Prof. Dr. Alfredo Vellido
Dr. Ana Candiota
Dr. Margarida Julia-Sape
Guest Editors

Manuscript Submission Information

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