Developed by the Zhejiang Society for Mathematical Medicine and the NMPA AI Medical Device Innovation Cooperation Platform, this is the first comprehensive framework establishing standardized requirements for sample diversity and data sufficiency in cervical LBC AI datase

A review published in Intelligent Oncology (Volume 2, Issue 3) provides a comprehensive framework for evaluating AI applications across the full cancer epidemiology continuum — from surveillance and data infrastructure through primary prevention, screening, prognosis, comparative effectiveness, and survivorship. Led by authors from Chongqing University, Monash University, and the University of Melbourne, the paper applies a diagnostic matrix that crosses three epidemiologic pillars (study population, measurement, and inference) with six stages of the AI lifecycle, from problem definition to post-deployment monitoring.

A scoping review published in Intelligent Oncology (Volume 2, Issue 3) provides the first systematic mapping of AI applications across cancer rehabilitation – a field with fragmented evidence despite rapid growth. Following PRISMA‑ScR guidelines, the authors from Chongqing University Cancer Hospital screened 3,032 records across eight databases and identified 49 studies that synthesise evidence on how AI can address persistent challenges in rehabilitation: resource limitations, workforce shortages, and the lack of personalised care.