Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models.

Artificial intelligence models match or exceed dermatologists in melanoma image classification. Less is known about their robustness against real-world variations, and clinicians may incorrectly assume that a model with an acceptable area under the receiver operating characteristic curve or related performance metric is ready for clinical use. Here, we systematically assessed the performance of dermatologist-level convolutional neural networks (CNNs) on real-world non-curated images by applying computational "stress tests".

Basivertebral Nerve Ablation for the Treatment of Vertebrogenic Pain.

Chronic low back pain affects a significant portion of patients worldwide and is a major contributor to patient disability; however, it is a difficult problem to diagnose and treat. The prevailing model of chronic low back pain has presumed to follow a discogenic model, but recent studies have shown a vertebrogenic model that involves the basivertebral nerve (BVN). Radiofrequency ablation of the BVN has emerged as a possible nonsurgical therapy for vertebrogenic low back pain.

The role of technology in melanoma screening and diagnosis.

Melanoma presents challenges for timely and accurate diagnosis. Expert panels have issued risk-based screening guidelines, with recommended screening by visual inspection. To assess how recent technology can impact the risk/benefit considerations for melanoma screening, we comprehensively reviewed non-invasive visual-based technologies.