The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice.

The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice. Semin Cutan Med Surg. 2019 Mar 01;38(1):E38-E42 Authors: Rotemberg V, Halpern A, Dusza S, Codella NC Abstract In the past decade, machine learning and artificial intelligence have made significant advancements in pattern analysis, including speech and natural language processing, image recognition, object detection, facial recognition, and action categorization. Indeed, in many of these applications, accuracy has reached or exceeded human levels of performance. Subsequently, a multitude of studies have begun to examine the application of these technologies to health care, and in particular, medical image analysis. Perhaps the most difficult subdomain involves skin imaging because of the lack of standards around imaging hardware, technique, color, and lighting conditions. In addition, unlike radiological images, skin image appearance can be significantly affected by skin tone as well as the broad range of diseases. Furthermore, automated algorithm development relies on large high-quality annotated image data sets that incorporate the breadth of this circumstantial and diagnostic variety. These issues, in combination with unique complexities regarding integrating artificial intelligence systems into a clinical workflow, have led to difficulty in using these systems to improve sensitivity and specificity of skin diagnostics in...
Source: Seminars in Cutaneous Medicine and Surgery - Category: Dermatology Tags: Semin Cutan Med Surg Source Type: research