Medical Dosimetrists

Generate radiation treatment plans, develop radiation dose calculations, communicate and supervise the treatment plan implementation, and consult with members of radiation oncology team.

The occupation "Medical Dosimetrists" has an automation risk of 49.2%, which is close to its estimated base risk of 50.0%. This moderate risk level arises because many of the tasks performed by medical dosimetrists depend heavily on technical and computational skills, where automation technologies are highly effective. For example, designing the arrangement of radiation fields to minimize exposure to critical structures, planning the use of beam modifying devices, and identifying bodily structures using imaging modalities are all tasks that can be systematically executed with advanced computer algorithms, machine learning models, and specialized software. These repetitive, protocol-driven tasks lend themselves well to automation, reducing the need for direct human involvement. However, not all aspects of the medical dosimetrist's role are easily automated. The top three most resistant tasks—educating patients on treatment plans and care, measuring radioactivity with monitoring devices, and developing complex treatment plans (such as for brachytherapy)—require high levels of interpersonal communication, practical judgement, and sophisticated decision-making. Education and patient communication are deeply personal and context-dependent, where empathy, adaptability, and emotional intelligence are crucial, thus making automation less viable. Similarly, measuring radioactivity or developing intricate brachytherapy plans necessitate critical thinking and nuanced interpretation of both technology and patient-specific circumstances. A key bottleneck in fully automating this occupation is the need for originality, albeit at a somewhat modest level (reported at 3.0% and 3.4% for relevant skills). Originality represents the ability to generate new approaches and adapt complex treatment plans to the unique characteristics of individual patients—something automation currently struggles to replicate. As a result, while software and technology can streamline and assist with many medical dosimetry tasks, human expertise remains irreplaceable in tailoring and explaining treatments, ensuring precision, and maintaining high standards of patient-centered care. This balance of automatable technical procedures and resistant human-centric skills explains why the occupation's automation risk falls just under the halfway mark.