Gastrointestinal Oncology: Management and Care

Gastrointestinal cancers are complex, with one of the many challenges being the difficulties surrounding diagnosis and treatment. The rapid adoption of Artificial Intelligence (AI) in many industries can be seen as a possible revolution to our healthcare systems and outcomes. As machine learning algorithms and medical professionals work alongside one another to benefit patients and improve treatments, we ask: how does this affect the prevention and treatment of gastrointestinal cancers?

While the use of computers and robotics may seem typical of the 21^st century, we invite researchers in this field to discuss how the limitations of technology can be pushed to reach new heights with the introduction of AI to assist with cancer screening, imaging, treatment plans, drug development, surgery and other various aspects of the cancer journey. This may also include when the active treatment period ends and remission is achieved, to give patients peace of mind and provide leading care in the future. It could also be to aid prevention of disease by creating algorithms of holistic living to optimise, diet, risk factors and inherited factors.

In order to highlight the role AI will play in gastrointestinal cancers, it is important to maintain a global, open-minded perspective. This is particularly in light of the challenges faced by different healthcare centers and providers. Each methodology and insight will be valuable to uncovering

The novel technology and algorithms are certainly appreciated, however this Article Collection will also look at other digital systems that may be taken for granted, such as telehealth appointments, and how these may be useful to treat GI cancers and manage the screening and surveillance of premalignancy.

This Article Collection will solicit articles related to the following subjects. However, we welcome all submissions related to the umbrella topic of machine learning and the use of technology in cancer diagnostics, imaging and treatment:

• Value of AI for cancer prediction, diagnostics and treatment, including digital twins, analysis of population-level cancer data, other types of machine learning, and influence of technology on personalized treatments
  • Assistance with making population-level changes adapted to each individual and associated genetic and lifestyle information
  • Impacts of AI for patient education and engagement
• Computer-driven treatments including adaptive radiotherapy, surgeries using robotics, CRISPR gene editing therapy and CAR-T immunotherapy, high-throughput drug screen systems
• Ethical considerations for the use of AI in healthcare settings (e.g., data privacy, consent, responsible use) and mitigation strategies for potential biases
• Benefits and challenges of telehealth appointments for cancer care
• Use of AI and technology in gastrointestinal cancer drug manufacturing and research

Instructions for Authors

The following Article Types will be considered: Research Article, Review Article, Case Report, Registered Report, Data Note, Method, Article Commentary, Patient Perspectives, and Plain Language Summary.

When submitting your article, please select the Article Collection, ‘Artificial intelligence-driven cancer care’ from the drop-down menu on the submission system.

Instructions for AuthorsSubmit an Article