检索结果-南通市图书馆

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

在线全文

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Exploring the role of N-acetyltransferases in diseases:a focus on N-acetyltransferase 9 in neurodegeneration

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第10期20卷 2862-2871页

作者： Prajakta Deshpande Anuradha Venkatakrishnan Chimata Amit singh Department of Biology University of DaytonDaytonOHUSA Premedical Program University of DaytonDaytonOHUSA Center for Tissue Regeneration and Engineering at Dayton(TREND) University of DaytonDaytonOHUSA Integrative Science and Engineering Center University of DaytonDaytonOHUSA Center for Genomic Advocacy(TCGA) Indiana State UniversityTerre HauteINUSA

Acetyltransferases,required to transfer an acetyl group on protein are highly conserved proteins that play a crucial role in development and *** acetylation is a common post-translational modification pivotal to basic cellular *** to 80%-90%of proteins are acetylated during translation,which is an irreversible process that affects protein structure,function,life,and *** this review,we have discussed the various N-acetyltransferases present in humans,their function,and how they might play a role in ***,we have focused on N-acetyltransferase 9 and its role in microtubule *** have shed light on how N-acetyltransferase 9 and acetylation of proteins can potentially play a role in neurodegenerative *** have specifically discussed the N-acetyltransferase 9-acetylation independent function and regulation of c-Jun N-terminal kinase signaling and microtubule stability during development and neurodegeneration.

关键词： acetyl-coenzyme A Alzheimer’s disease animal models cell death drosophila eye human disease c-Jun N-terminal kinase signaling N-Acetyltransferases N-acetyltransferase 9 neurodegeneration

Fibrinogen’s potential role in connecting cerebrovascular abnormalities with glymphatic dysfunction in Alzheimer’s disease

在线全文

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第1期20卷 203-204页

作者： Vishal singh Arnab Choudhury Hyung Jin Ahn Department of Pharmacology Physiology and NeurosciencesRutgers-New Jersey Medical SchoolNewarkNJUSA Brain Health Institute Rutgers UniversityPiscatawayNJUSA

Alzheimer’s disease(AD)stands out as the primary manifestation of age-related dementia,portraying a chronic neurodegenerative disorder distinguished by the accumulation of fibrillar amyloid-β(Aβ)plaques and neurofibrillary tangles of hyperphosphorylated ***,from a clinical standpoint,AD presents itself as a complex condition with a spectrum of dysfunctions rather than a singular pathological *** often-overlooked aspect of the disease is the presence of extensive cerebrovascular abnormalities,given that the majority of AD patients experience altered cerebral blood flow,damaged vasculature,increased microinfarcts and *** models of AD further support this observation,showing cerebrovascular dysfunction such as impaired cerebral blood flow and altered cerebrovascular reactivity(Tataryn et al.,2021;Gareau et al.,2023).

关键词： cerebrovascular dysfunction Alzheimer

发达国家纵向整合临床实习模式的发展及其对我国医学教育的启示

在线全文

学校读者我要写书评

暂无评论

中华医学教育杂志 2020年第9期40卷 748-752页

作者：李鸿鹤 David A Hirsh tara a singh Yamini Saravanan Rachel Hathaway Bianca Shagrin Elizabeth Gaufberg Arundhati Ghosh 刘君李扬龄闻德亮中国医科大学国际医学教育研究院沈阳110122 哈佛大学医学院剑桥健康联盟马萨诸塞州剑桥市02139 中国医科大学沈阳110122

临床实习是医学生将理论知识转化为临床能力和深入临床环境学习的重要途径。纵向整合临床实习模式目前是一种创新性的临床教学方法和理念,它将连续性作为教学原则,很好地解决了原有临床实习中缺乏医疗连续性、课程连续性和教学指导连续... 详细信息

临床实习是医学生将理论知识转化为临床能力和深入临床环境学习的重要途径。纵向整合临床实习模式目前是一种创新性的临床教学方法和理念,它将连续性作为教学原则,很好地解决了原有临床实习中缺乏医疗连续性、课程连续性和教学指导连续性的问题,越来越多的医学院应用此种模式进行临床教学改革。本文对该实习模式的核心内涵、意义和哈佛剑桥模式及其发展与衍变进行阐述,并结合中国医学教育的实际需求进行分析,认为纵向整合临床实习模式可以提高我国临床医生培养质量,促进基层医疗人才队伍建设,增强住院医师规范化培训效果,有助于我国医学教育改革发展。

关键词：临床医学教育教育连续性纵向整合临床实习模式中国启示

Synthetic data as an investigative tool in hypertension and renal diseases research

在线全文

学校读者我要写书评

暂无评论

World Journal of Methodology 2025年第1期15卷 9-13页

作者： Aleena Jamal Som singh Fawad Qureshi Sidney Kimmel Medical College Thomas Jefferson UniversityPhiladelphiaPA 19107United States School of Medicine University of Missouri Kansas CityKansasMO 64106United States Division of Nephrology and Hypertension Mayo ClinicRochesterMN 55905United States

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in *** nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient *** is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension ***,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

关键词： Synthetic data Artificial intelligence Nephrology Blood pressure Research Editorial

A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAURABH R.KIRAN D.singh R.VAISH V.S.CHAUHAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. Hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IHSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the C0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(HR), helicoidal exponential(HE), helicoidal semi-circular(HS), linear helicoidal(LH), and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

关键词：

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

Structural and optical properties of green emitting Y_(2)SiO_(5):Tb^(3+) and Gd_(2)SiO_(5):Tb^(3+) nanoparticles for modern lighting applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Rare Metals 2021年第11期40卷 3289-3298页

作者： Sitender singh Devender singh Department of Chemistry Maharshi Dayanand UniversityRohtak 124001India

The optical and structural properties of Tb^(3+)-doped yttrium and gadolinium oxyorthosilicate(Y_(2)SiO_(5) and Gd_(2)SiO_(5)) phosphors were *** samples were synthesized via sol-gel combustion method using organic *** phase purity and structural properties of the samples were determined via combined approach of powder X-ray diffraction,Fourier transformation infrared(FTIR) and transmission electron microscopy(TEM).X-ray measurements revel monoclinic crystal lattice with P_(21/c) symmetry for both M_(2)SiO_(5)(pure host) and M_(2)SiO_(5):Tb^(3+)(doped) silicates,irrespective of the nature of metal(Y or Gd),presence or absence of Tb^(3+)in lattice and change in calcination temperature up to 1050℃.FTIR analysis was applied to confirm the bonding of prepared *** appearance of bands corresponding to SiO_(4) tetrahedra(880-1020 cm^(-1)) suggest the layered structure and support the diffraction *** micrographs confirm the synthesis of spherical nanoparticles with filled morphology,narrow size distribution and slightly agglomerated crystallites of the *** elemental composition of prepared materials was determined using energy dispersive X-ray *** spectra show peaks only for elements assimilated within the host *** photoluminescence(PL) emission spectra of Tb^(3+)-doped samples show ^(5)D_(4)→^(7)F_(J)(J=3-6) transitions under 254 *** dominant peak at 544 nm for ^(5)D_(4)→^(7)F_(5) transition is responsible for the emission of green light on ultraviolet-visible excitation in both the Tb^(3+)-doped host *** to advantageous properties like intense PL and high crystallinity,these nanophosphors could possess potential applications in the mercury free lighting sources and optoelectronic devices.

关键词： Structural Optical Silicates Luminescence Optoelectronic