Accuracy and Interpretability: Key Considerations
The impressive accuracy of DEEP-squared has already been demonstrated, with algorithms exhibiting expert performance in a variety of clinical diagnostic tasks across numerous image-centric specialties. However, the interpretability of these models is equally important, as it provides assurance that the model is behaving as intended and alerts clinicians to potential biases in the machine vision system.
Minimizing Physician Liability
In the context of malpractice suits, the unique capabilities and functions of AI and machine vision, especially when combined with advances in their interpretability, create an opportunity to argue that the technology minimizes physician liability. This is because the technology can potentially reduce human error and increase the accuracy of diagnoses, thereby reducing the likelihood of malpractice claims.