The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human–computer collaboration in clinical practice.

EPILUMINESCENCE microscopy (ELM; in vivo cutaneous surface microscopy, dermoscopy, dermatoscopy, and magnified oil immersion diascopy) is an in vivo, noninvasive technique that has disclosed a new dimension of the clinical morphologic features of pigmented skin lesions using different incident light magnification systems with an oil immersion technique.¹

In comparison with inspection with the unaided eye, dermoscopy (dermatoscopy¹) improves the accuracy of the diagnosis of pigmented skin lesions.² The improvement of dermoscopy is most evident for small and inconspicuous melanomas³ and for pigmented basal cell carcinoma.⁴ Because dermoscopic criteria are more specific and the number of differential diagnoses is significantly lower, pigmented skin lesions are easier to diagnose than nonpigmented lesions. The most common types of skin cancers, however, are usually nonpigmented. A previous study showed that dermoscopy also improves the accuracy of the diagnosis of nonpigmented lesions, although the improvement was less pronounced than for pigmented lesions.⁵ The proportion of correct diagnoses by expert raters increased from 41.3% with the unaided eye to 52.7% with dermoscopy. The improvement of nonexperts was less pronounced.