Precision Oncology: AI-Driven Innovations in Hepatic and Pancreatic Cancer Diagnosis and Prognosis

Hepatic and pancreatic oncology is at the forefront of medical research due to the persistently high morbidity and mortality associated with these cancers. Despite advances in screening and therapy, early detection remains challenging, and survival rates are dismally low compared to other malignancies. In recent years, artificial intelligence (AI) has emerged as a promising tool for overcoming these barriers. Fueled by breakthroughs in machine learning, deep learning, radiomics, and genomics, AI is beginning to transform traditional diagnostic pathways, identify novel biomarkers, and enable truly personalized medicine. Initial studies have demonstrated encouraging results in the automated detection of lesions, risk stratification, and predictions of therapeutic response, underlining a significant shift in how clinicians approach these malignancies.Yet, while rapid progress is being made, several challenges persist. Questions remain about the generalizability, safety, and interpretability of AI models when integrated into real-world clinical workflows. Furthermore, disparities in data quality, limited collaborative datasets, and ethical concerns about privacy and bias continue to hinder broad adoption. There is a growing need for research that not only introduces novel AI algorithms and pipelines but also rigorously evaluates their performance in diverse patient populations, addresses their explainability, and accounts for the nuanced ethical landscape of AI-driven decision-making in oncology.This Research Topic aims to spotlight the latest advances in artificial intelligence that are shaping the landscape of hepatic and pancreatic cancer diagnosis, prognosis, and treatment. By encouraging multidisciplinary collaboration between data scientists and clinical experts, the goal is to accelerate the translation of AI innovation from concept to clinic, thereby improving patient outcomes and reducing disease burden.To gather further insights in the domain of AI-enabled hepatic and pancreatic oncology, we invite articles focusing on research, innovation, and application of AI, while keeping the clinical context central and emphasizing interpretability and ethics. We welcome contributions addressing, but not limited to, the following themes:- Early cancer detection and screening using AI-based tools- AI-driven biomarker identification and genomics integration- Prognostic modeling and survival prediction with machine learning- Personalization of therapeutic strategies through predictive analytics- Model interpretability, transparency, and clinical trust- Data heterogeneity, federated learning, and multi-institutional collaboration- Ethical, legal, and social implications of AI in oncology Topic editors: ACHIN JAIN, Weiwei Jiang, Neha Gupta Source: https://www.frontiersin.org/research-topics/72137/precision-oncology-ai-driven-innovations-in-hepatic-and-pancreatic-cancer-diagnosis-and-prognosis