Enhancing Precision in Cancer Treatment: AI-Driven Innovations in Imaging
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 68
Special Issue Editor
Interests: rare tumors; data science and computational biology; brain and spine cancer; head and neck cancer; genitourinary tumors; re-irradiation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are delighted to announce the call for submissions to a Special Issue of Cancers focusing on the theme of "Enhancing Precision in Cancer Treatment: AI-Driven Innovations in Imaging". In the realm of oncology, the integration of artificial intelligence (AI) into imaging technologies has revolutionized cancer diagnosis, treatment planning, and monitoring.
This Special Issue aims at exploring the intersection of AI and medical imaging in advancing precision in cancer care. We invite original research articles and reviews that delve into the following topics:
- Application of AI in early cancer detection and diagnosis;
- AI-driven innovations in radiomics and radiogenomics for personalized treatment;
- Role of AI in predicting treatment response and patient outcomes;
- Enhancing image-guided interventions through AI algorithms;
- Ethical considerations and challenges in implementing AI in cancer imaging.
All submissions will undergo a thorough peer-review process to ensure scientific rigor and relevance to the field. We encourage submissions from experts in medical imaging, oncology, AI, and related disciplines to share their insights and advancements in this rapidly evolving field.
By amalgamating cutting-edge research and clinical experiences, this Special Issue aims at propelling the frontiers of precision medicine in oncology and paving the way for more tailored and effective cancer treatments. Your valuable contributions are instrumental in shaping the future of cancer care through AI-powered innovations in medical imaging.
Should you have any queries, require additional information, or seek assistance during the submission process, please feel free to contact us. We are committed to facilitating your participation and ensuring the success of this Special Issue.
Thank you for your interest and dedication to advancing precision in cancer treatment through AI-driven innovations in imaging.
Warm regards,
Dr. Andra Valentina Krauze
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 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. 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.
Keywords
- precision medicine
- artificial intelligence
- medical imaging
- cancer treatment
- AI-driven innovations
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