It's easy to find out how many calories are in a Twinkie. But how about in a tweet? A team of scientists have invented a new instrument for measuring just that: the caloric content of social media posts - like tweets.
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Teach a Computer to Recognize AML
Researchers have developed the first computer machine-learning model to accurately predict which patients diagnosed with acute myelogenous leukemia, or AML, will go into remission following treatment for their disease and which will relapse. The computer was trained using bone marrow data and medical histories of AML patients, as well as blood data from healthy individuals.
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One Step Closer to Personalized Antibiotic Treatment
Taking antibiotics to fight an infection won't necessarily solve your problems. Often, natural occurring bacteria in the gut harbor several resistance genes. This means that the gut bacteria may exchange genes with the infectious bacteria, resulting in antibiotic resistance. Therefore, knowing the resistome - i.e. the pool of resistance genes present in the gut microbiota - can improve treatment immensely.
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Hand-held Breath Monitor to Detect Flu
Perena Gouma, a professor in the Materials Science and Engineering Department at The University of Texas at Arlington, has published an article in the journal Sensors that describes her invention of a hand-held breath monitor that can potentially detect the flu virus.
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Brain-Computer Interface Allows Completely Locked-in People to Communicate
A brain-computer interface that can decipher the thoughts of people who are unable to communicate could revolutionize the lives of those living with complete locked-in syndrome according to a new paper published in PLOS Biology. Counter to expectations, the participants in the study reported being "happy" despite their condition.
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Wearable AI System can Detect a Conversation's Tone
It's a fact of nature that a single conversation can be interpreted in very different ways. For people with anxiety or conditions such as Asperger's, this can make social situations extremely stressful. But what if there was a more objective way to measure and understand our interactions?
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Discrepancy Between What Symptoms Patients Report, What Appears in Electronic Medical Record
Researchers found significant inconsistencies between what symptoms patients at ophthalmology clinics reported on a questionnaire and documentation in the electronic medical record, according to a study published online by JAMA Ophthalmology. The percentage of office-based physicians using any electronic medical record (EMR) increased from 18 percent in 2001 to 83 percent in 2014.
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