Machine Learning in Precision Oncology: Innovations and Applications

Dear Colleagues,

Recent advances in machine learning and generative models have opened new fields of research in relation to precision oncology, enabling the development of highly personalized, data-driven approaches to cancer diagnosis, prognosis, and treatment. This Special Issue aims to highlight the latest research and innovations at the intersection of bioengineering, artificial intelligence, and oncology, with a focus on how machine learning and generative models—such as GANs, VAEs, diffusion models, and large language models—are reshaping cancer research and clinical workflows.

We invite contributions that highlight novel methodologies, translational research, and practical implementations of machine learning and generative AI in oncology. Topics of interest include—but are not limited to—cancer subtype classification, risk prediction models, treatment response forecasting, integration of multi-omics data, drug discovery, biomarker identification, AI-assisted pathology, and real-time decision support systems. Submissions showcasing interdisciplinary approaches that bridge machine learning, bioengineering, and clinical oncology are particularly encouraged.

This Special Issue aims to bring together researchers, clinicians, and engineers to present advances that push the boundaries of personalized cancer care through the application of intelligent systems.

Dr. Sheida Nabavi
Dr. Jun Bai
Guest Editors

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 short 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly 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 2700 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.