Artificial intelligence (AI) is reshaping surgical oncology, with applications spanning preoperative planning, intraoperative guidance, and postoperative surveillance. While advances in radiomics, pathomics, multimodal data fusion, computer vision, augmented/extended reality, and intelligent robotics have accelerated over the past decade, important questions remain regarding clinical effectiveness, generalizability, safety, equity, and cost-effectiveness.

This Research Topic seeks to consolidate high-quality evidence and highlight methodologically rigorous innovations that advance patient-centered, trustworthy, and value-conscious AI in surgical oncology.

We welcome Original Research, Systematic Reviews, Mini Reviews, Meta-Analyses, Clinical Trials, Methods/Technology Reports, and Perspectives.

Topics of interest include, but are not limited to:

- Precision surgery and patient selection: Preoperative risk stratification using imaging, pathology, genomics, and clinical data; Decision support for indications/contraindications and treatment sequencing with systemic therapies; Management of anatomically complex or high-risk cases
- Intraoperative guidance and workflow intelligence: Computer vision for tissue classification, margin and vascular/perfusion assessment, structure recognition, and error/near-miss detection; AI-enabled navigation with AR/XR overlays, instrument tracking, and surgical phase recognition; Integration with robotic systems and energy devices
- Data, models, and interoperability: Dataset curation, harmonization, and standards (e.g., DICOM, FHIR); Approaches to domain shift and model drift; device/vendor-agnostic performance; Model calibration, uncertainty estimation, and human–AI teaming
- Methodology, validation, and reporting: External, out-of-distribution, multicenter, and multinational validation; Robustness to missing data, noise, and distributional changes; Sensitivity/ablation analyses and transparent reporting aligned with community guidelines

Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.We welcome Original Research, Systematic Reviews, Mini Reviews, Meta-Analyses, Clinical Trials, Methods/Technology Reports, and Perspectives. Topics of interest include, but are not limited to:

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Artificial Intelligence in Surgical Oncology: Current Applications, Challenges, and Future Directions