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Aims & Scope

“AI in Precision Oncology is more than a scientific or medical journal; it is a mission-driven initiative to harness the power of AI in improving oncology care.” – Dr. Douglas Flora, Editor-in-Chief

AI in Precision Oncology is the only peer-reviewed journal dedicated to the advancement of artificial intelligence applications in clinical and precision oncology. Spearheaded by Editor-in-Chief Douglas Flora, MD and supported by a diverse and accomplished team of international experts, the Journal provides a high-profile forum for cutting-edge research and frontmatter highlighting important research and industry-related advances rapidly developing within the field.  

The use of AI in oncology has the potential to revolutionize cancer care, from early detection to precision medicine. AI can assist in analyzing complex data, such as genomics, imaging, and electronic health records, to improve cancer diagnosis and treatment planning. Moreover, AI can help predict treatment responses, identify new drug targets, and facilitate clinical trials. The Journal's scope includes all aspects of AI in oncology, from basic research to clinical implementation.

AI in Precision Oncology publishes original research articles, reviews, and perspectives on the application of artificial intelligence (AI) in cancer research, diagnosis, and treatment, bringing together researchers, clinicians, and industry experts to share their knowledge and experience in this rapidly evolving field. The Journal helps professionals in the field of oncology understand how artificial intelligence and technology solutions can be applied in an evidence-based, ethical, and thoughtful manner. Overall, the Journal seeks to promote AI's responsible and effective use in oncology, benefiting both healthcare providers and patients. 

AI in Precision Oncology coverage includes:

  • AI algorithms for cancer detection, diagnosis, and prognosis
  • AI-based biomarkers for cancer screening and diagnosis
  • AI-assisted imaging analysis for tumor detection and segmentation
  • AI-guided treatment planning and personalized therapy
  • AI-enabled drug discovery and development
  • Machine learning and deep learning in cancer research
  • Natural language processing for electronic health record analysis
  • Ethical and regulatory issues in AI in oncology


AI in Precision Oncology is under the editorial leadership of Editor-in-Chief Douglas Flora, MD, Executive Medical Director, Oncology Services, St. Elizabeth, and supported by a diverse and accomplished team of experts, including David Penberthy, MD, MBA, Associate Professor of Radiation Oncology, Penn State Health; Nikhil Thaker, MD, Chief Medical Informatics Officer, Arizona Oncology; and Scott Penberthy, Managing Director of AI at Google.

The views, opinions, findings, conclusions and recommendations set forth in any Journal article are solely those of the authors of those articles and do not necessarily reflect the views, policy or position of the Journal, its Publisher, its editorial staff or any affiliated Societies and should not be attributed to any of them.