Artificial intelligence in healthcare refers to the use of complex algorithms designed to conduct certain tasks in an automated manner. Artificial intelligence has a transformative power in radiation oncology to improve the quality and efficiency of patient care, given the increase in volume and complexity of digital data, as well as the multi-faceted and highly technical nature of this field of medicine. However, artificial intelligence alone will not be able to fix healthcare's problem, because new technologies bring unexpected and potentially underappreciated obstacles. The inclusion of multicentre datasets, the incorporation of time-varying data, the assessment of missing data as well as informative censoring and the addition of clinical utility could significantly improve artificial intelligence models. Standardisation plays a crucial, supportive and leading role in artificial intelligence. Clinical trials are the most reliable method of demonstrating the efficacy and safety of a treatment or clinical approach, as well as providing high-level evidence to justify artificial intelligence. The National Surgical Adjuvant Breast and Bowel Project, the Radiation Therapy Oncology Group and the Gynecologic Oncology Group collaborated to form NRG Oncology (acronym NRG derived from the names of the parental groups). NRG Oncology is one of the adult cancer clinical trial groups containing radiotherapy specialty of the National Cancer Institute's Clinical Trials Network (NCTN). Standardisation from NRG/NCTN has the potential to reduce variation in clinical treatment and patient outcome by eliminating potential errors, enabling broader application of artificial intelligence tools. NCTN, NRG and Imaging and Radiation Oncology Core are in a unique position to help with standards development, advocacy and enforcement, all of which can benefit from artificial intelligence, as artificial intelligence has the ability to improve trial success rates by transforming crucial phases in clinical trial design, from study planning through to execution. Here we will examine: (i) how to conduct technical and clinical evaluations before adopting artificial intelligence technologies, (ii) how to obtain high-quality data for artificial intelligence, (iii) the NCTN infrastructure and standards, (iv) radiotherapy standardisation for clinical trials and (v) artificial intelligence applications in standardisation. (c) 2021 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
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