Shaping the Future of Oncology: The Role of Generative AI in Clinical and Research Environments
A special issue of Current Oncology (ISSN 1718-7729).
Deadline for manuscript submissions: 30 September 2025 | Viewed by 50
Special Issue Editors
Interests: bladder cancer; prostate cancer; renal cell carcinoma; robot-assisted surgery; biomarker-based oncology studies; prognostic outcome models; translational research; multicenter projects in genitourinary oncology research
Special Issues, Collections and Topics in MDPI journals
Interests: generative artificial intelligence in medicine; uro-oncology
Interests: urological oncology; bladder cancer; prostate cancer; urologic surgery; cancer research; predictive biomarkers; robot-assisted surgery
Special Issue Information
Dear Colleagues,
The emergence of generative artificial intelligence (AI) marks a pivotal transformation in oncology, with the potential to redefine clinical practice, therapeutic approaches, and research paradigms. This Special Issue of Current Oncology seeks to investigate the diverse and rapidly expanding applications of generative AI in the field of oncology, covering advancements in diagnostics, breakthroughs in treatment modalities, and the optimization of clinical decision making. We invite submissions that showcase how generative AI is being harnessed to enhance cancer diagnostics, individualize treatment regimens, and support decision-making processes for both clinicians and patients through AI-driven decision intelligence.
We particularly welcome manuscripts that evaluate the efficacy of AI-powered tools for cancer patients and explore their clinical applications. Contributions are encouraged from researchers and practitioners highlighting original studies, review articles, case reports, and innovative methodologies demonstrating how AI is addressing the intricate challenges of cancer care, especially how generative AI bridges the gap between research and clinical implementation, fostering a more seamless, integrated, and efficient oncological landscape.
This Special Issue aims to provide a comprehensive exploration of the present and future roles of generative AI in oncology, offering key insights into its transformative potential for cancer care and research. We look forward to your pioneering contributions to this dynamic and swiftly evolving field, which promises to set new standards for oncological treatment and research.
Prof. Dr. Matthias May
Dr. Emily Rinderknecht
Dr. Maximilian Haas
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Current Oncology 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 2200 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.
Keywords
- generative AI in oncology
- AI-driven cancer diagnostics
- personalized cancer treatment
- AI in clinical decision making
- oncology research innovation
- AI-assisted therapeutic strategies
- cancer care technology
- patient-centered AI tools and apps
- translational oncology and AI
- future of oncology
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