Multimodal Artificial Intelligence/Machine Learning Applications in Malignant Tumors: Diagnosis, Prognosis, and Management
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Causes, Screening and Diagnosis".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 10
Special Issue Editors
Interests: artificial intelligence; medical imaging; cancer; cerebrovascular disease
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) and machine learning (ML) models have shown promising results in the extraction of subtle imaging features that are beyond human perception from medical images, improving the detection of malignancies, risk stratification, and response assessments. The integration of multi-modal imaging data with clinical, molecular, and genomic information through AI/ML models further adds to the potential of precision oncology. However, the clinical translation of these technologies requires their rigorous validation, interpretability, and integration into complex healthcare workflows.
This Special Issue of Cancers highlights cutting-edge research on AI/ML applications across the continuum of cancer care, from automated detection and segmentation to outcome prediction and the optimization of therapy. We invite contributions addressing methodological advances, clinical implementation, multi-institutional validation, and ethical considerations, aiming to bridge the gap between technical innovation and real-world impact in oncologic imaging.
Dr. Sam Payabvash
Dr. Stefan Haider
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- radiomics
- cancer imaging
- malignancy
- survival
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