首页|Research from University of Zurich Has Provided New Data on Artificial Intellige nce (Canine Cerebrospinal Fluid Analysis Using Two New Automated Techniques: The Sysmex XN-V Body Fluid Mode and an Artificial-Intelligence-Based Algorithm)
Research from University of Zurich Has Provided New Data on Artificial Intellige nce (Canine Cerebrospinal Fluid Analysis Using Two New Automated Techniques: The Sysmex XN-V Body Fluid Mode and an Artificial-Intelligence-Based Algorithm)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on artificial in telligence. According to news reporting originating from Zurich, Switzerland, by NewsRx correspondents, research stated, “Cerebrospinal fluid analysis is an imp ortant diagnostic test when assessing a neurological canine patient.” The news correspondents obtained a quote from the research from University of Zu rich: “For this analysis, the total nucleated cell count and differential cell c ounts are routinely taken, but both involve time-consuming manual methods. To in vestigate faster automated methods, in this study, the Sysmex XN-V body fluid mo de and the deep-learning-based algorithm generated by the Olympus VS200 slide sc anner were compared with the manual methods in 161 canine cerebrospinal fluid sa mples for the total nucleated cell count and in 65 samples with pleocytosis for the differential counts. Following incorrect gating by the Sysmex body fluid mod e, all samples were reanalyzed with manually set gates. The Sysmex body fluid mo de then showed a mean bias of 15.19 cells/mL for the total nucleated cell count and mean biases of 4.95% and -4.95% for the two-part differential cell count, while the deep-learning-based algorithm showed mean bi ases of -7.25%, -0.03% and 7.27% for th e lymphocytes, neutrophils and monocytoid cells, respectively. Based on our find ings, we propose that the automated Sysmex body fluid mode be used to measure th e total nucleated cell count in canine cerebrospinal fluid samples after making adjustments to the predefined settings from the manufacturer.”
University of ZurichZurichSwitzerlan dEuropeAlgorithmsArtificial IntelligenceEmerging TechnologiesMachine L earning
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