AI-driven imaging biomarkers for sensory cue integration during melanoma screening (Conference Presentation)

Early diagnosis of melanomas is the most effective means of improving melanoma prognosis. We can arm the non-expert screeners with artificial intelligence but most artificial intelligence methods are somewhat impractical in a clinical setting given the lack of transparency. To provide a quantitative and algorithmic approach to lesion diagnosis while maintaining transparency, and to supplement the clinician rather than replace them, our digital analysis provides visual features, or, “imaging biomarkers” that can both be used in machine learning and visualized too.