首页|University of Pittsburgh School of Medicine Reports Findings in Spina Bifida (Ma chine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer A bility In Spina Bifida)
University of Pittsburgh School of Medicine Reports Findings in Spina Bifida (Ma chine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer A bility In Spina Bifida)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Spina Bifida is the subject of a report. According to news reporting from Pittsburgh,Pennsylvania, by NewsRx jou rnalists, research stated, “To determine which statistical techniquesenhance ou r ability to predict ambulation and transfer ability in people with spina bifida (SB). Retrospectivecohort study SETTING: 35 United States outpatient SB clinic sites PARTICIPANTS: individuals(n=4,589) with SB ages 5-73 (median age =13.59) INTERVENTION: not applicable MEASURE: ambulationability, which consisted of th e following categories: community ambulators, household ambulators,therapeutic ambulators, and non-ambulators SECONDARY OUTCOME: wheelchair transfer ability, a sdefined by the ability to transfer in and out of a wheelchair unassisted A Rec urrent Neural Network (RNN)utilizing a multilayer perceptron discarded 76 cases during case processing, resulting in 4513 that were runthrough the RNN.”
PittsburghPennsylvaniaUnited StatesNorth and Central AmericaAlgorithmsCyborgsDrugs and TherapiesEmerging T echnologiesHealth and MedicineMachine LearningSpina BifidaSpinal Dysraph ism
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