About this Research Topic
The amalgamation of big data and artificial intelligence has been widely utilized in various cancer fields, including basic cancer research, particularly in molecular biological mechanisms, metabolic reprogramming, tumor biology, and clinical transformation research (such as cancer prediction, early diagnosis methods, and development of new treatment methods). The systematic and objective data provided by big data and artificial intelligence can guide diagnosis, optimize clinical treatment decisions, and have a far-reaching impact on clinical transformation.
This research topic aims to explore novel biomarkers and predictive models that predict prognosis, treatment efficacy, and toxic side effects in cancer patients. We welcome submissions including, but not limited to:
(1) Clinical research investigating novel biomarkers and their comprehensive predictive models for cancer treatment (including chemotherapy, radiation therapy, targeted therapy, and immunotherapy) and prognosis.
(2) Original research investigating inflammatory and immune factors associated with various types of cancer, particularly breast and gastrointestinal cancer.
(3) Reviews and meta-analyses of effective biomarkers and predictive models in cancer treatment and prognosis.
(4) Cancer-related basic research and clinical transformation research based on big data and artificial intelligence.
(5) Accurate detection and diagnosis of early cancer, intelligent prediction models of neoadjuvant treatment, and targeted treatment response of cancer.
Keywords: Biomarkers, Cancer, Immunotherapy, Inflammatory factors, meta-analyses
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.