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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

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

AI devs claim they’ve created a robot that demonstrates a ‘primitive form of empathy’

Columbia University researchers have developed a robot that displays a “glimmer of empathy” by visually predicting how another machine will behave. The robot learns to forecast its partner’s future actions and goals by observing a few video frames of its actions The researchers first programmed the partner robot to move towards green circles in a playpen of around 3×2 feet in size. It would sometimes move directly towards a green circle spotted by its cameras, but if the circles were hidden by an obstacle, it would either roll towards a different circle or not move at all. After the observer robot watched the… This story continues at The Next Web

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