16-Year-Old Engineer Works to Improve Spinal Surgery Using Machine Learning and Computer Vision Krithik Ramesh of Greenwood Village, Colorado, Wins $75,000 Top Prize at Intel International Science.
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Using machine learning and computer vision, the project helps orthopedic surgeons achieve greater accuracy for screw placement during spinal surgery. Based on Ramesh’s tests, this method has the potential to decrease operating time by at least 30 minutes, reduce physical therapy recovery time by four weeks and diminish the negative side.
Inductive logic programming (ILP) is a form of machine learning which learns computer programs from input/output examples of a target program. To improve learning efficiency, ILP systems use background knowledge (i.e. auxiliary functions such as partition and append).
Society for Science & the Public is a non-profit organization dedicated to public engagement in scientific research and education. The company was founded by Edward W. Scripps and William Emerson Ritter in 1921 and is headquartered in Washington, DC.
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16-Year-Old Engineer Works to Improve Spinal Surgery Using Machine Learning and Computer Vision (wire.mpelembe.net) submitted 26 days ago by smbale to r/MachineLearning comment
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Shooting Star and Milky Way over Goblin Valley National Park in Green River, Utah. Photo Credit: Bret Webster ~ The Milky Way is seen in the distance over a collection of hoodoos,
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16-Year-Old Engineer Works to Improve Spinal Surgery Using Machine Learning and Computer Vision Krithik Ramesh, 16, of Greenwood Village, Colorado, was awarded first place for developing a machine learning technology for orthopedic surgeons at this year’s Intel International Science and Engineering Fair (ISEF), a program of Society for Science & the Public.
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