The Use of Artificial Intelligence in Predicting Response to Cancer Therapy

Dear Colleagues,

Artificial intelligence (AI) is rapidly transforming oncology by enabling deeper, multimodal understanding of how patients respond to cancer therapies. Advances in machine learning, knowledge graph models, multimodal embeddings, and agentic clinical decision-support systems are accelerating our ability to integrate genomics, pathology, imaging, clinical trajectories, and real-world data at an unprecedented scale. As precision oncology expands, the ability to predict therapeutic benefit, resistance patterns, toxicity risk, and dynamic treatment response has become central to improving outcomes and reducing disparities.

This Special Issue aims to highlight cutting-edge AI approaches that enhance response prediction across targeted therapies, immunotherapy, cell and gene therapies, radiotherapy, and combination strategies. We welcome original research, methodological innovations, clinical validation studies, and comprehensive reviews that advance trustworthy, explainable, and clinically actionable AI for oncology. Submissions addressing equity, real-world implementation, federated learning, regulatory considerations, and human–AI collaboration are particularly encouraged.

We look forward to your contributions to this rapidly evolving field.

Dr. Arturo Loaiza-Bonilla
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.