首页|Findings on Machine Learning Discussed by Investigators at City University of Lo ndon (Evaluating the Effectiveness of Non-invasive Intracranial Pressure Monitor ing Via Near-infrared Photoplethysmography Using Classical Machine Learning Meth ods)
Findings on Machine Learning Discussed by Investigators at City University of Lo ndon (Evaluating the Effectiveness of Non-invasive Intracranial Pressure Monitor ing Via Near-infrared Photoplethysmography Using Classical Machine Learning Meth ods)
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Investigators publish new report on Ma chine Learning. According to news reporting out of London, United Kingdom, by Ne wsRx editors, the research stated, "This study investigates the feasibility of u tilising photoplethysmography signals to estimate continuous intracranial pressu re (ICP) values in patients with traumatic brain injury. A clinical dataset was compiled, comprising synchronised data from a non-invasive optical sensor and an invasive gold standard ICP monitor from 27 patients." Financial support for this research came from George Daniels Educational Trust-G eorge Daniels Doctoral Studentship.
LondonUnited KingdomEuropeCyborgsEmerging TechnologiesMachine LearningCity University of London
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