Hackathon Computer Vision App Proves AI’s Use in Spotting Cancer
At the recent TechCrunch Disrupt SF 2017 hackathon, researchers presented a promising proof of concept on an AI-based system –named Doctor Hazel– that analyzes images of skin abnormalities and determines with about an 85% accuracy rate whether or not the patient may have skin cancer and should seek the opinion of a real doctor. While only in its earliest phases, Doctor Hazel’s demonstrated sucsess could lead soon to more advanced and accurate technologies that could assist or eventually all but replace more traditional means of skin cancer screening. Read more about this technology and other attempts at using AI to diagnose skin cancer at MobiHealthNews:
Engineers participating in a hackathon last weekend demonstrated an artificial intelligence that they say could someday detect cancerous moles, TechCrunch reports. Although the program is currently in its infancy, the team hopes that enough user submissions could allow Doctor Hazel to predict skin cancer with at least 90 percent accuracy.
After one day and thousands of image downloads, the AI is identifying cancer at an 85 percent success rate, the team said during a presentation at TechCrunch Disrupt’s San Francisco 2017 hackathon. However, the team has launched a beta and is inviting users to submit their own photos to improve Doctor Hazel’s performance.
“There’s a huge problem in getting AI data for medicine … no one wants to share,” Mike Borozdin, developer of Doctor Hazel, told TechCrunch. “But amazing results are possible. The more people share, the more accurate the system becomes.”
Doctor Hazel gauges 8,000 variables when viewing a sample to determine whether the image is of a mole, melanoma, another type of cancer, or nothing. The team plans to have an app accompany the platform, as well as an image capturing device that could someday be made available for sale.
Apps, mobile platforms, and camera devices designed to evaluate moles and estimate skin cancer risk have a long history filled with successes and failures.