Deep Learning Algorithm Diagnoses Skin Cancer Better than Human Dermatologists - The New Stack

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The days of a depending on a human doctor may soon be numbered, as the future of the health industry looks increasingly like an AI-assisted scenario. Researchers and startups are developing artificially intelligent systems that are capable of diagnosing disease using a patient's breath and even from the emotional inflection of their voice. Someday, your smartphone may help you and your doctor determine whether a strange-looking lesion on your skin is cancerous or not, thanks to a team of Stanford University scientists that have developed a deep learning algorithm tailored just for the task. Led by Sebastian Thrun, an adjunct professor at the Stanford Artificial Intelligence Laboratory, the team found that their diagnostic tool, which builds upon the same classification technique used by Google to differentiate between images of cats and dogs, performed as well or better than 21 board-certified dermatologists. Their findings were detailed in a recent paper published in Nature.


Artificial intelligence used to identify skin cancer Stanford News

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It's scary enough making a doctor's appointment to see if a strange mole could be cancerous. Imagine, then, that you were in that situation while also living far away from the nearest doctor, unable to take time off work and unsure you had the money to cover the cost of the visit. In a scenario like this, an option to receive a diagnosis through your smartphone could be lifesaving. A dermatologist uses a dermatoscope, a type of handheld microscope, to look at skin. Computer scientists at Stanford have created an artificially intelligent diagnosis algorithm for skin cancer that matched the performance of board-certified dermatologists.


Artificial intelligence used to identify skin cancer Stanford News

#artificialintelligence

It's scary enough making a doctor's appointment to see if a strange mole could be cancerous. Imagine, then, that you were in that situation while also living far away from the nearest doctor, unable to take time off work and unsure you had the money to cover the cost of the visit. In a scenario like this, an option to receive a diagnosis through your smartphone could be lifesaving. A dermatologist uses a dermatoscope, a type of handheld microscope, to look at skin. Computer scientists at Stanford have created an artificially intelligent diagnosis algorithm for skin cancer that matched the performance of board-certified dermatologists.


Computers trounce pathologists in predicting lung cancer type, severity

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Computers can be trained to be more accurate than pathologists in assessing slides of lung cancer tissues, according to a new study by researchers at the Stanford University School of Medicine. The researchers found that a machine-learning approach to identifying critical disease-related features accurately differentiated between two types of lung cancers and predicted patient survival times better than the standard approach of pathologists classifying tumors by grade and stage. "Pathology as it is practiced now is very subjective," said Michael Snyder, PhD, professor and chair of genetics. "Two highly skilled pathologists assessing the same slide will agree only about 60 percent of the time. This approach replaces this subjectivity with sophisticated, quantitative measurements that we feel are likely to improve patient outcomes."


'Eureka moment': AI software programmed to spot skin cancer by checking pics of moles

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The researchers tested the AI against 130,000 images, comparing the results to diagnoses of 21 clinicians. They say the result showed the software could detect the cancer with a high degree of accuracy. The findings were published in the academic journal Nature. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," said Sebastian Thrun from the Stanford Artificial Intelligence Laboratory, in a statement published by the university's website. "That's when our thinking changed.