This AI can tell if you have prostate cancer by looking at your pee

Researchers at the Korean Institute of Science and Technology (KIST) recently developed a machine for detecting prostate cancer that only needs 20 minutes of your time and a few ounces of your pee to achieve near 100-percent accuracy. Human oncologists are only about 30% accurate when it comes to detecting the disease. This is a big deal. Background: Detecting prostate cancer is, quite literally, a pain in the ass. Under the current paradigm the disease is confirmed through a combination of lab work and invasive diagnostics. This involves a painful biopsy procedure where surgeons remove a tissue sample from the…

This story continues at The Next Web

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This ‘AI doctor’ can assess skin melanoma as accurately as human dermatologists

Scientists from the University of Gothenburg have developed an algorithm that assesses the severity of skin melanoma as accurately as dermatologists. The system was developed to help doctors determine the stage that a skin cancer has reached. While patients often independently find melanomas by spotting a new mole or a change in an existing one, even dermatologists can struggle to decide whether it’s invasive or not. The researchers suspected that AI could assist them with the task. [Read: How Polestar is using blockchain to increase transparency] They classified the melanomas with a convolutional neural network (CNN), a powerful method of analyzing images that’s proven… This story continues at The Next Web

Scientists developed an AI system for predicting human psychosis

A team of European scientists led by researchers from the Max Planck institute recently developed the world’s first cybernetic system for predicting psychosis onset in high-risk patients. According to the NIH, about three percent of the general population (data is US-specific) will experience psychosis in their lifetimes. To put that in perspective, the odds you’ll be stung by a bee are approximately six million to one. Unfortunately, predicting psychosis in high-risk patients is a difficult task. The current paradigm requires intensive diagnosis by trained professionals at a specialized medical facility, something most of the world’s population lacks immediate access to.… This story continues at The Next Web

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