Files
Download Full Text (518 KB)
Abstract
Oncologic diagnosticians are physicians who specialize in interpreting diagnostic exams to diagnose cancer in patients. Software companies have been developing artificial intelligence (AI) systems to interpret these exams to diagnose cancer. These AI systems may affect the traditional role of oncologic diagnosticians if they were to be implemented in the clinical setting. Therefore, I set out to answer my research question: How will AI and machine learning systems impact the roles of oncologic diagnosticians in diagnosing cancer and the patient-physician relationship? By analyzing surveys and studies, I examined the attitudes of oncologic diagnosticians versus cancer patients toward implementing AI systems in healthcare. Furthermore, I compared the diagnosing accuracies of AI systems and oncologic diagnosticians to uncover which screening entity is superior. I also evaluated specific diagnostic workflows to explore the practical implementations of AI systems in oncology. I investigated AI systems’ potential effects on the oncologic patient-physician relationship. Moreover, I reviewed the ethics of utilizing AI systems in cancer diagnostics to determine if AI implementation is practical. I observed positive attitudes amongst oncologic diagnosticians and patients towards the usage of AI systems, especially if these systems are to be used as assistance programs for physicians. In terms of screening accuracy and the impact on patient-physician relationships, studies showed a lack of consensus. There are also several ethical implications present, but policies and guidelines can be implemented to regulate and manage the usage of AI systems as diagnostic tools. In summary, AI and machine learning systems seem unlikely to replace oncologic diagnosticians. Instead, studies suggest that these devices will assist physicians to reduce diagnostic errors and improve accuracy and reliability. The extent to which the patient-physician relationship is influenced by AI systems seems likely to depend on the physician and their style of practice.
Publication Date
2022
Keywords
Artificial Intelligence, Machine Learning, Oncology, Cancer, Diagnostic, Screening, Patient-Physician Relationship, Predicting Accuracy
Disciplines
Bioethics and Medical Ethics | Public Health
Current Academic Year
Freshman
Faculty Advisor/Mentor
Faye Prichard
Rights
© The Author(s)