Comprehensive Summary
This article examines the usage of artificial intelligence in the form of clinical decision support systems for oncologists when making treatment plans for cancer patients with complex medical histories. As cancer care becomes increasingly complicated, it is important for clinicians to make individualized decisions for their patients. The authors of this article make a case for AI-powered clinical decision support systems as informative aids when physicians are considering results of pharmaceutical trials, guidelines such as the National Comprehensive Cancer Network, and individual patient genomic data to make faster, more accurate decisions, reducing doubts and errors, and decreasing the cognitive load associated with creating treatment plans. The authors caution the use of these support systems and emphasize that they must be used carefully, making sure they are validated properly, tested thoroughly, and user-friendly when implemented. It is also worth mentioning that they hope to enhance human performance with these platforms, not replace human judgement. The article concludes that future oncologists will likely practice in partnership with clinical decision support systems, combining clinical expertise and empathy with artificial intelligence support.
Outcomes and Implications
This article has significant implications on oncologists seeking premiere treatment for their patients. These support systems could assist clinicians in navigating the growing complexity of cancer care by summarizing known clinical trials, personalized patient information, and known genomic data into a treatment plan that is specific to the patient based on input from the clinician. If done correctly, this will be revolutionary for physicians, improving patient outcomes and limiting errors while allowing the physician to help more patients than ever before. With AI by a clinician’s side, the world of medicine will be enhanced by the knowledge and power of supportive models instead of replacing human intelligence and decision making.