Cognitive Biases contribute significantly to diagnostic and treatment errors. Physicians are constantly concerned with gathering and interpreting evidence, taking action and evaluating decisions. One of the most critical aspects for Radiation Oncology doctors is delineation. This process involves accurately outlining the target tumors and identifying the organs at risk (OARs) to create effective radiation therapy plans. This work is fundamental in achieving the delicate balance between effectively treating the cancer and preserving the patient's quality of life by protecting vital organs and minimizing side effects. To make such a decision in the UCSD radiation oncology department, the doctors rely on two key factors: 1) the imaging data with AI detection around the tumor and organs, and 2) their own personal knowledge and experience. Drawing from previous cases they have handled, how different tumors behave, and how they appear on imaging scans. Steenbakker et al. showed that there were significant differences in the delineation styles among radiation oncologists, indicating variability in how they defined the Gross Tumor Volume (GTV) for lung cancer patients [1]. This reliance on initial data and personal expertise can make them susceptible to anchoring bias. Anchoring bias occurs when decision-makers fixate on an initial piece of information, limiting the exploration of alternative hypotheses and potentially impacting the accuracy and effectiveness of the treatment plan.