首页|New Machine Learning Study Results Reported from Tel Aviv Medical Center (A mach ine learning contest enhances automated freezing of gait detection and reveals t ime-of-day effects)
New Machine Learning Study Results Reported from Tel Aviv Medical Center (A mach ine learning contest enhances automated freezing of gait detection and reveals t ime-of-day effects)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news originating from the Tel Aviv Medi cal Center by NewsRx correspondents, research stated, "Freezing of gait (FOG) is a debilitating problem that markedly impairs the mobility and independence of 3 8-65% of people with Parkinson's disease." Financial supporters for this research include Michael J. Fox Foundation For Par kinson's Research. Our news correspondents obtained a quote from the research from Tel Aviv Medical Center: "During a FOG episode, patients report that their feet are suddenly and inexplicably ‘glued' to the floor. The lack of a widely applicable, objective F OG detection method obstructs research and treatment. To address this problem, w e organized a 3-month machine-learning contest, inviting experts from around the world to develop wearable sensor-based FOG detection algorithms. 1,379 teams fr om 83 countries submitted 24,862 solutions. The winning solutions demonstrated h igh accuracy, high specificity, and good precision in FOG detection, with strong correlations to gold-standard references. When applied to continuous 24/7 data, the solutions revealed previously unobserved patterns in daily living FOG occur rences."
Tel Aviv Medical CenterCyborgsEmergi ng TechnologiesMachine Learning
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