首页|Shanghai Jiao Tong University Reports Findings in Epilepsy (Diagnosis of epileps y by machine learning of high-performance plasma metabolic fingerprinting)
Shanghai Jiao Tong University Reports Findings in Epilepsy (Diagnosis of epileps y by machine learning of high-performance plasma metabolic fingerprinting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Central Nervous System Diseases and Conditions - Epilepsy is the subject of a report. According to new s reporting out of Shanghai, People's Republic of China, by NewsRx editors, rese arch stated, "Epilepsy is a chronic neurological disorder that causes a major th reat to public health and the burden of disease worldwide. High-performance diag nostic tools for epilepsy need to be developed to improve diagnostic accuracy an d efficiency while still missing." Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, "Herein, we utilized nanoparticle-enhanced laser desorption/ionizati on mass spectrometry (NELDI MS) to acquire plasma metabolic fingerprints (PMFs) from epileptic and healthy individuals for timely and accurate screening of epil epsy. The NELDI MS enabled high detection speed ( 30 s per sample), high through put (up to 384 samples per run), and favorable reproducibility (coefficients of variation <15 %), acquiring high-performed PMF s. We next constructed an epilepsy diagnostic model by machine learning of PMFs, achieving desirable diagnostic capability with the area under the curve (AUC) v alue of 0.941 for the validation set. Furthermore, four metabolites were identif ied as a diagnostic biomarker panel for epilepsy, with an AUC value of 0.812-0.8 60."
ShanghaiPeople's Republic of ChinaAs iaBrain Diseases and ConditionsCentral Nervous System Diseases and Condition sCyborgsDiagnostics and ScreeningEmerging TechnologiesEpilepsyHealth a nd MedicineMachine Learning
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