[Artificial intelligence-enabled advances in gastric cancer imaging: current status, challenges, and prospective strategies].

Insights into artificial intelligence-based digital pathology in hepatobiliary and pancreatic cancer

Artificial intelligence (AI)-driven digital pathology has emerged as a promising approach for improving diagnosis, prognostic assessment, and treatment decision-making in hepatobiliary and pancreatic cancers (HPCs). By leveraging whole-slide imaging and deep learning, AI enables high-throughput and reproducible analysi...

Use of artificial intelligence in the management of cholangiocarcinoma: Current applications, evidence, and future perspectives

Current and developing uses of AI in cholangiocarcinoma, ranging from ambiguous biliary strictures to tailored treatment options, are outlined, and progress in this field is compared with the more mature experience of radiology, pathology, and gastrointestinal endoscopy are compared.

Artificial intelligence in endometrial cancer: multimodal deep learning and future perspectives in precision gynecologic oncology — a structured narrative review

This structured narrative review summarizes AI applications in endometrial cancer, focusing on ultrasound imaging, radiomics, digital pathology, multimodal deep-learning, explainable AI, prognostic modeling, clinical translation, and future perspectives in personalized care.

Artificial intelligence in prostate cancer diagnosis and management: state-of-the-art approaches and emerging innovations.

This review summarizes the current state of AI applications in the diagnosis, risk stratification, and treatment of prostate cancer, highlighting recent advances and emerging opportunities in this ever-changing field.

[Application of transformer in intelligent diagnosis and treatment of peritoneal metastasis: current status and prospects].

Artificial intelligence in non-small cell lung cancer: transforming diagnosis, treatment, and prognostic evaluation

Non-small cell lung cancer (NSCLC) is characterized by profound biological heterogeneity, frequently leading to late-stage diagnosis, recurrence, or metastasis. Conventional clinical pathways heavily depend on subjective visual interpretations, invasive tissue biopsies, and experience-based medical models that constrai...