Why Dermatologists Should Support Artificial Intelligence?
Dermatologists should embrace AI and drive how it is utilized – be the captain of the plane (technology) and the passenger (patient). In 2019, a group of German researchers found that AI can improve accuracy and efficiency of specialists in classifying skin cancer based on dermoscopic images. Current research involves using supervised learning on known outcomes to determine inputs to predict them. In dermatology, think of identifying melanoma from clinical or dermoscopic images or predicting metastasis risk from digitized pathology slides.
@papiya However, there are currently no universal guidelines on how large an AI dataset needs to be to yield accurate results. In the dermatology literature, most AI datasets range between 600 and 14,000 examples with a large study-specific variation in performance. Misleading results can result from unanticipated training errors. The AI network may learn its intended task or an unrelated situational cue. For example, you can use great images to predict melanoma, but you may have an unintended poor outcome related to images that have, say, a ruler inside of them clustered within the melanoma diagnoses.