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Magnetic resonance spectroscopy findings of brain olfactory areas in patients with COVID-19-related anosmia:A preliminary comparative study

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World Journal of Otorhinolaryngology-Head and Neck Surgery 2024年第2期10卷 105-112页

作者： Shadman Nemati mohammad haghani dogahe Alia Saberi Naghi Ramezani Pejman Kiani Tofigh Yaghubi Kalurazi Ehsan Kazemnejad Leili Sara Seddighi Abbas Monsef Department of Otolaryngology and Head and Neck Surgery School of MedicineOtorhinolaryngology Research CenterGuilan University of Medical SciencesRashtIran Guilan Road Trauma Research Center Guilan University of Medical SciencesRashtGuilanIran Department of Neurology Neuroscience Research CenterPoursina HospitalGuilan University of Medical SciencesRashtIran Department of Radiology Pars International HospitalGuilan ProvinceIran Department of Neuroscience and Addiction Studies School of Advanced Technologies in MedicineTehranIran Department of Infectious Diseases Razi Clinical Research Development UnitRazi HospitalGuilan University of Medical SciencesRashtIran Center of Magnetic Resonance Research Department of Radiation OncologyUniversity of Minnesota Medical SchoolMinneapolisMinnesotaUSA

Objectives:2019 novel coronavirus disease(COVID-19)infection is commonly associated with olfactory dysfunctions,but the basic pathogenesis of these complications remains *** study seeks to evaluate the value of magnetic resonance spectroscopy(MRS)in determining the molecular neurometabolite alterations within the main brain olfactory areas in patients with COVID-19-related ***:In a cross-sectional study,seven patients with persistent COVID-19-related anosmia(mean age:29.57 years)and seven healthy volunteers(mean age:27.28 years)underwent MRS in which N-acetyl-aspartate(NAA),choline(Cho),creatine(Cr),and their ratios were measured in the anterior cingulate cortex,dorsolateral prefrontal cortex,orbitofrontal cortex(OFC),insular cortex,and ventromedial prefrontal *** were analyzed using TARQUIN software(version 4.3.10),and the results were compared with an independent sample t-test and nonparametric Mann-Whitney test based on the normality of the MRS data ***:The mean duration of anosmia before imaging was 8.5 months in COVID-19-related anosmia *** analysis elucidated a significant association between MRS findings within OFC and COVID-19-related anosmia(P_(disease)<0.01),and NAA was among the most important neurometabolites(P_(interaction)=0.006).Reduced levels of NAA(P<0.001),Cr(P<0.001)and^(NAA)/Cho ratio(P=0.007)within OFC characterize COVID-19-related ***:This study emphasizes that MRS can be illuminating in COVID-19-related anosmia and indicates a possible association between central nervous system impairment and persistent COVID-19-related anosmia.

关键词： anosmia COVID-19 magnetic resonance spectroscopy neuroimaging olfaction

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New supervised learning classifiers for structural damage diagnosis using time series features from a new feature extraction technique

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Earthquake Engineering and Engineering Vibration 2022年第1期21卷 169-191页

作者： Masoud haghani Chegeni mohammad Kazem Sharbatdar Reza Mahjoub Mahdi Raftari Department of Civil Engineering Khorramabad BranchIslamic Azad UniversityKhorramabadIran*** Faculty of Civil Engineering Semnan UniversitySemnanIran***

The motivation for this article is to propose new damage classifiers based on a supervised learning problem for locating and quantifying damage.A new feature extraction approach using time series analysis is introduced to extract damage-sensitive features from auto-regressive *** approach sets out to improve current feature extraction techniques in the context of time series *** coefficients and residuals of the AR model obtained from the proposed approach are selected as the main features and are applied to the proposed supervised learning classifiers that are categorized as coefficient-based and residual-based *** classifiers compute the relative errors in the extracted features between the undamaged and damaged ***,the abilities of the proposed methods to localize and quantify single and multiple damage scenarios are verified by applying experimental data for a laboratory frame and a four-story steel *** analyses are performed to validate the superiority of the proposed methods over some existing *** show that the proposed classifiers,with the aid of extracted features from the proposed feature extraction approach,are able to locate and quantify damage;however,the residual-based classifiers yield better results than the coefficient-based ***,these methods are superior to some classical techniques.

关键词： structural damage diagnosis statistical pattern recognition feature extraction time series analysis supervised learning classification

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