AI Rivals Person Dermatologists at Detecting Skin Cancer

An artificial intelligence algorithm powered by a database of more than 130,000 images of skin lesions can detect skin cancer in addition to a human dermatologist, researchers state. AI Rivals Person Dermatologists at Detecting Skin Cancer

The AI, developed by a group from Stanford University, has a couple of significant differences from the normal advanced neural networks which have witnessed increasing use among medical researchers. For starters, it is not built from scratch, but rather harnesses an existing Google database of 1.28 million objects. That means it knows how to classify things, so the researchers could spend less time on training the algorithm and also more on satisfying its sensitivity and accuracy. AI Rivals Person Dermatologists at Detecting Skin Cancer.

The end result is a computing tool that could drastically simplify the procedure for diagnosing skin cancer in regions of the world that don’t have hospitals or clinics. The algorithm has been tested against the diagnoses of 21 board-certified dermatologists, along with the investigators also said it matched the humans’ performance.

Since the very first step in skin cancer detection is a visual review, theoretically all the AI would need is a good-enough excellent photo of this patient, possibly taken with a smartphone. There are still a few wrinkles to iron out before that happens, however, the most important of which is the algorithm is presently designed for supercomputers, not smartphones. However, its founders are optimistic.

“Advances in computer-aided classification of benign versus malignant skin lesions may greatly help dermatologists in improved diagnosis for challenging lesions and provide better management alternatives for patients,” Stanford professor of dermatology Susan Swetter stated in a announcement . “However, rigorous prospective validation of this algorithm is essential before it can be implemented in clinical practice, by patients and professionals alike.”

Read : Deep Learning

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