Application of Artificial Intelligence-Based Approaches in Cancer Diagnosis, Treatment and Prognosis
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 1220
Special Issue Editor
Interests: cancer genomics; computational biology; deep learning in cancer research; long non-coding RNA; drug resistance; single cell; spatial transcriptomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advancements in artificial intelligence (AI) have revolutionized various sectors and are rapidly reshaping cancer research and personalized clinical care. Big data and our powerful computing capacity have led to the transformative potential of AI-based approaches, particularly deep learning and generative AI, in the field of oncology, specifically in cancer diagnosis, treatment, and prognosis. These applications have demonstrated remarkable capabilities in early detection and accurate diagnosis, optimizing cancer treatment protocols, predicting disease progression, recurrence, and patient survival, and in drug discovery, repurposing, and combination therapy strategies. We expect that the integration of AI technologies in cancer care will enhance the precision, efficiency, and personalization of patient management, ultimately improving clinical outcomes and quality of life for cancer patients.
This Special Issue invites research that explores the development and application of AI-based diagnostic tools, including imaging analysis, histopathological evaluations, and biomarker identification. Contributions that delve into AI-assisted treatment planning, including radiotherapy, chemotherapy, and immunotherapy, are sought. Research on AI models that predict treatment responses, suggest personalized therapy regimens, and manage treatment-related side effects are of particular interest. Generative AI approaches that can accelerate the identification of de novo anticancer compounds, simulate drug interactions, and predict novel therapeutic compounds hold significant promise in this area. We also seek contributions on multimodal AI algorithms that integrate digital pathology, radiology, genomics, and electronic medical records to generate comprehensive prognostic insights, facilitate patient monitoring, follow-up care, and long-term outcome predictions.
Additionally, we invite discussions on the ethical, legal, and practical implications of deploying AI in cancer care. Submissions that address data privacy, algorithmic bias, and the integration of AI with existing clinical workflows are highly valued.
This Special Issue aspires to present a diverse collection of pioneering research that showcases the transformative impact of AI, particularly generative AI and deep learning, in oncology, fostering innovation and collaboration among researchers, clinicians, and technologists in the fight against cancer
I look forward to receiving your contributions.
Dr. Wei Wu
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
- cancer genomics
- artificial intelligence
- machine learning
- deep learning
- tumor microenvironment
- graph-based convolutional neural network
- computational cancer biology
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