(CNN)Even though the phrase “image recognition technologies” conjures visions of high-tech surveillance, these tools may soon be used in medicine more than in spycraft.
A team of Stanford researchers trained a computer to identify images of skin cancer moles and lesions as accurately as a dermatologist, according to a new paper published in the journal Nature.
In the future, this new research suggests, a simple cell phone app may help patients diagnose a skin cancer — the most common of all cancers in the United States — for themselves.
“Our objective is to bring the expertise of top-level dermatologists to places where the dermatologist is not available,” said Sebastian Thrun, senior author of the new study, founder of research and development lab Google X and an adjunct professor at Stanford University. He added that those who live in developing countries do not have the same level of care as can be found in the US and other industrialized nations.
“You can grow up to be in your 20s and never have seen skin cancer, and you can go to medical school and just see a few examples on slides, and all of a sudden, you’re going to be pretty good at recognizing that,” he said.
No computer has been trained to do the same, but computer visual systems may detect subtleties within digital photographs unseen by the human eye, the researchers pointed out.
The moment of truth came when the researchers presented previously unseen images to their algorithm. Would their artificial intelligence system be able to recognize both the most common and the most deadly types of skin cancer: malignant carcinomas and melanomas, respectively?
“This algorithm performed as well as board-certified dermatologists at several key diagnostic tasks,” Esteva said.
Notably, the computer was able to “diagnose multiple different kinds of skin cancer, not just melanoma, and we were able to do this with regular clinical images, rather than with specialized dermoscopic images,” said Roberto Novoa, a co-author of the study and a dermatologist at Stanford Medicine.
He explained that doctors commonly use a dermatoscope, a specialized tool, to examine the skin for cancer. This tool enables a view from a similar distance with similar lighting and magnification, for easier diagnosis.
Though the algorithm lacked access to this expensive tool, its performance still equaled the accuracy of 21 dermatologists.
Though Thrun, Esteva and their colleagues warn that real testing in a clinical setting — a doctor’s office — is still needed, they believe their research might be expanded to include other areas of medicine, such as ophthalmology, radiology and pathology.
With 6.3 billion smartphone subscriptions estimated to be in use by 2021 (PDF), the researchers noted, their new system, in the form of an app, could provide low-cost universal access to diagnostic care.
Paging Dr. McCoy
Science fiction is rife with visions of technology replacing human doctors. Dr. Leonard McCoy used a portable diagnostic device known as a tricorder to determine the medical condition of the USS Enterprise crew members in the “Star Trek” TV series and movies, recalled Dr. Sancy A. Leachman, a dermatologist and chairwoman of the department of dermatology at Oregon Health and Science University, and Glenn Merlino, a senior investigator at the National Cancer Institute, in their published commentary on the new study.
Though still “fanciful,” machines capable of non-invasive diagnosis are “becoming a reality,” wrote Leachman and Merlino, neither of whom was involved in the new study.
That said, at least one issue still requires more investigation when it comes to a skin cancer-detecting automated system.
According to Leachman and Merlino, it is not known whether the artificial intelligence system featured in the new study can distinguish between similar-looking diseases. For example, a system would need to be able to identify melanoma versus benign seborrhoeic keratosis — basically, a non-cancerous wart.
“Even the benign growths can be associated with certain syndromes and diseases that only a physician that has been clinically trained for detecting can diagnose,” said Dr. Jill Waibel, a dermatologist and owner of the Miami Dermatology and Laser Institute.
Waibel, who did not participate in the study, added that “medical Imaging has dramatically transformed the practice of medicine,” especially her field of dermatology. Yet despite many exciting developments, all of the new imaging systems are still being studied and explored for optimal uses, she said.
For many scientists, though, “Star Trek” still beckons: a future filled with machines that learn with each corrected mistake, improving their performance over time.
“This is a very specific study, and it has a very encouraging result,” Thrun said. But he warned that before this research might be leveraged into anything resembling a tricorder, “we would have to run many more studies.”