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Machines learn to detect breast cancer Nov 5th 2013, 15:36 Software that can recognize patterns in data is commonly used by scientists and economics. Now, researchers in the US have applied similar algorithms to help them more accurately diagnose breast cancer. Computer-aided image analysis for breast tumor diagnosis Nov 4th 2013, 19:24 Researchers hope radiologists will be able to routinely incorporate computer-aided image analysis and diagnosis in identifying tumor characteristics and forming patient-specific breast cancer treatment plans. Their approach uses data to identify how tumor characteristics apply to disease states, which could lead to the comparison of a tumor's characteristics with thousands of similar cases. Bitcoin open to takeover, researchers discover with new algorithm Nov 4th 2013, 16:22 A major flaw that has gone unrealized until now leaves the $1.5 billion Bitcoin market open to manipulation and a potential takeover, according to a new study by computer scientists. Computer model anticipates crime hot spots Nov 4th 2013, 14:55 Sociologists working with law enforcement officials produced a computer model that predicts, by census block group, where burglaries are likely to occur. Synaptic transistor learns while it computes Nov 2nd 2013, 13:55 It doesn't take a Watson to realize that even the world's best supercomputers are staggeringly inefficient and energy-intensive machines. Our brains have upwards of 86 billion neurons, connected by synapses that not only complete myriad logic circuits; they continuously adapt to stimuli, strengthening some connections while weakening others. We call that process learning, and it enables the kind of rapid, highly efficient computational processes that put Siri and Blue Gene to shame. New way to monitor induced comas Oct 31st 2013, 21:55 After suffering a traumatic brain injury, patients are often placed in a coma to give the brain time to heal and allow dangerous swelling to dissipate. These comas, which are induced with anesthesia drugs, can last for days. During that time, nurses must closely monitor patients to make sure their brains are at the right level of sedation -- a process that scientists now describe as "totally inefficient." An automated system could offer better control of patients' brain states.

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