检索结果-内蒙古大学图书馆

A biosensing system employing nanowell microelectrode arrays to record the intracellular potential of a single cardiomyocyte

引用

Microsystems & Nanoengineering 2022年第3期8卷 185-198页

作者： Yuting Xiang Haitao Liu Wenjian Yang Zhongyuan xu Yue Wu Zhajian Tang Zhjing Zhu Zhiyong Zeng Depeng Wang Tianxing Wang Ning Hu Diming Zhang Department of Obstetrics and Gynecology Affiliated Dongguan People's HospitalSouthern Medical UniversityDongguan 523058China Research Center for Inelligent Sensing Systems Zhejiang LaboratoryHangzhou 311100China Research Center for Humanoid Sensing Zhejiang LaboratoryHangzhou 311100China Key Laboratory of Novel Target and Drug Study for Neural Repair of Zhejiang Province School of MedicineSchool of Computer&Computing ScienceZhejiang University City CollegeHangzhou 310015China School of Brain Science and Brain Medicine Zhejiang UniversityHangzhou 310058China School of Automation Nanjing University of Science and TechnologyNanjing 210094China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China E-Link Care Meditech Co. LtdHangzhou 310011China ZJU-Hangzhou Global Scientific and Technological Innovation Center Department of ChemitryZhejiang UniversityHangzhou 310058China

Electrophysiological recording is a widely used method to investigate cardiovascular pathology,pharmacology and developmental *** arrays record the electrical potential of cells in a minimally invasive and highthroughput ***,commonly used microelectrode arays primarily employ planar microelectrodes and cannot work in applications that require a recording of the intracellular action potential of a single *** this study,we proposed a novel measuring method that is able to record the intracellular action potential of a single cardiomyocyte by using a nanowell patterned microelectrode array(NWMEA).The NWMEA consists of five nanoscale wells at the center of each circular planar *** pulse electroporation was applied to the NWMEA to penetrate the cardiomyocyte membrane,and the intracellular action potential was continuously *** intracellular potential recording of cardiomyocytes by the NWMEA measured a potential signal with a higher quality(213.76±25.85%),reduced noise root-mean-square(~33%),and higher signal-to-noise ratio(254.36±12.61%)when compared to those of the extracellular *** to previously reported nanopillar microelectrodes,the NWMEA could ensure single cell electroporation and acquire high-quality action potential of cardiomyocytes with reduced fabrication *** NWMEA-based biosensing system is a promising tool to record the intracellular action potential of a single cell to broaden the usage of microelectrode arrays in electrophysiological investigation.

关键词： arrays potential record

来源：评论

学校读者我要写书评

暂无评论

Robust peer-to-peer learning via secure multi-party computation

引用

Journal of Information and Intelligence 2023年第4期1卷 341-351页

作者： Yongkang Luo Wenjian Luo Ruizhuo Zhang Hongwei Zhang Yuhui Shi Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies School of Computer Science and TechnologyHarbin Institute of TechnologyShenzhen 518055China Peng Cheng Laboratory Shenzhen 518055China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model ***-to-peer(P2P)federated learning further improves the robustness of the system,in which there is no server and each client communicates directly with the *** secure aggregation,secure multi-party computing(SMPC)protocols have been utilized in peer-to-peer ***,the ideal SMPC protocols could fail when some clients drop *** this paper,we propose a robust peer-to-peer learning(RP2PL)algorithm via SMPC to resist clients dropping *** improve the segmentbased SMPC protocol by adding a check and designing the generation method of random seg*** RP2PL,each client aggregates their models by the improved robust secure multi-part computation protocol when finishes the local *** results demonstrate that the RP2PL paradigm can mitigate clients dropping out with no significant degradation in performance.

关键词： Federated learning Swarm learning Secure multi-party computation Peer-to-peer learning

来源：评论

学校读者我要写书评

暂无评论

brain Connectivity Deviates by Sex and Hemisphere in the First Episode of Schizophrenia'-A Route to the Genetic Basis of Language and Psychosis? (vol 45, pg 484, 2018)

引用

SCHIZOPHRENIA BULLETIN 2019年第6期45卷 1381-1381页

作者： Wang, Qiang Mental Health Center and Psychiatric Laboratory the State Key Laboratory of Biotherapy West China Hospital of Sichuan University Chengdu PR ChinaWest China Brain Research Center West China Hospital of Sichuan University Chengdu PR China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai PR ChinaKey Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University) Ministry of Education PR China Life Science Research Center School of Life Science and Technology Xidian University Xi’an PR ChinaEngineering Research Center of Molecular and Neuro Imaging Ministry of Education School of Life Science and Technology Xidian University Xi’an PR ChinaSchool of Computer Science and Technology Xidian University Xi’an PR China POWIC University Department of Psychiatry Warneford Hospital Oxford UK Department of Computer and Information Sciences Temple University Philadelphia PA Robarts Research Institute University of Western Ontario & Lawson Health Research Institute London ON CanadaCentre for Translational Neuroimaging Institute of Mental Health University of Nottingham Nottingham UK Mental Health Center and Psychiatric Laboratory the State Key Laboratory of Biotherapy West China Hospital of Sichuan University Chengdu PR ChinaWest China Brain Research Center West China Hospital of Sichuan University Chengdu PR China Mental Health Center and Psychiatric Laboratory the State Key Laboratory of Biotherapy West China Hospital of Sichuan University Chengdu PR ChinaWest China Brain Research Center West China Hospital of Sichuan University Chengdu PR China Mental Health Center and Psychiatric Laboratory the State Key Laboratory of Biotherapy West China Hospital of Sichuan University Chengdu PR ChinaWest China Brain Research Center West China Hospital of Sichuan University Chengdu PR China Mental Health Center and Psychiatric Laboratory the State Key Laboratory of Biotherapy West China Hospital of Sichuan Uni

Schizophrenia is genetic in origin and associated with a fecundity disadvantage. The deficits in schizophrenia have been attributed to variation related to the human capacity for language or brain laterality. How sex influences the relative connectivity of the 2 hemispheres is a route to understanding these 2 functions. Using resting-state functional magnetic resonance imaging (fMRI) we searched for sex- and hemisphere-specific changes in whole-brain functional-connectivity in multi-site datasets (altogether 672 subjects including 286 patients, all right-handed) in the first-episode schizophrenia (illness duration ≤ 1 year, mostly drug naive) and in chronic stages of schizophrenia (illness duration > 1 year), respectively. We used meta-analyses to integrate data from different sources concerning individuals at the same illness stage. We found first-episode male patients are predominantly left-lateralized in aberrant connectivity with a focus on Broca’s area. Female patients show a lesser degree of lateralization than males, but to the right particularly in orbital frontal cortex. In the chronic stage, the focus of aberrant connectivity shifted from anterior to posterior structures with prominent involvement of the thalamus and pre- and post-central gyri bilaterally and in both sexes. While the “deviant connectivity” is right-sided in both the first-episode and the chronic stages in females, in males there is a shift between stages from the left to the right hemisphere. We hypothesized that the pathophysiology of schizophrenia may lie in the interaction between sex and lateralization, ie, in genetic mechanisms located on the X and Y chromosomes, intrinsic to the evolution of language.

关键词： resting-state fMRI whole-brain functional connectivity analysis sex-effect lateralization language PCDH11XY sexual selection

来源：评论

学校读者我要写书评

暂无评论

Meta ordinal regression forest for learning with unsure lung nodules

arXiv

引用

arXiv 2020年

作者： Lei, Yiming Zhu, Haiping Zhang, Junping Shan, Hongming Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Shanghai Center for Brain Science and Brain-inspired Technology Shanghai201210 China

Deep learning-based methods have achieved promising performance in early detection and classification of lung nodules, most of which discard unsure nodules and simply deal with a binary classification—malignant vs benign. Recently, an unsure data model (UDM) was proposed to incorporate those unsure nodules by formulating this problem as an ordinal regression, showing better performance over traditional binary classification. To further explore the ordinal relationship for lung nodule classification, this paper proposes a meta ordinal regression forest (MORF), which improves upon the state-of-the-art ordinal regression method, deep ordinal regression forest (DORF), in three major ways. First, MORF can alleviate the biases of the predictions by making full use of deep features while DORF needs to fix the composition of decision trees before training. Second, MORF has a novel grouped feature selection (GFS) module to re-sample the split nodes of decision trees. Last, combined with GFS, MORF is equipped with a meta learning-based weighting scheme to map the features selected by GFS to tree-wise weights while DORF assigns equal weights for all trees. Experimental results on LIDC-IDRI dataset demonstrate superior performance over existing methods, including the state-of-the-art DORF. © 2020, CC BY.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels

arXiv

引用

arXiv 2022年

作者： Lei, Yiming Zhu, Haiping Zhang, Junping Shan, Hongming The Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China The Shanghai Center for Brain Science and Brain-inspired Technology Shanghai200031 China

The performance of medical image classification has been enhanced by deep convolutional neural networks (CNNs), which are typically trained with cross-entropy (CE) loss. However, when the label presents an intrinsic ordinal property in nature, e.g., the development from benign to malignant tumor, CE loss cannot take into account such ordinal information to allow for better generalization. To improve model generalization with ordinal information, we propose a novel meta ordinal regression forest (MORF) method for medical image classification with ordinal labels, which learns the ordinal relationship through the combination of convolutional neural network and differential forest in a meta-learning framework. The merits of the proposed MORF come from the following two components: a tree-wise weighting net (TWW-Net) and a grouped feature selection (GFS) module. First, the TWW-Net assigns each tree in the forest with a specific weight that is mapped from the classification loss of the corresponding tree. Hence, all the trees possess varying weights, which is helpful for alleviating the tree-wise prediction variance. Second, the GFS module enables a dynamic forest rather than a fixed one that was previously used, allowing for random feature perturbation. During training, we alternatively optimize the parameters of the CNN backbone and TWW-Net in the metalearning framework through calculating the Hessian matrix. Experimental results on two medical image classification datasets with ordinal labels, i.e., LIDC-IDRI and Breast Ultrasound Dataset, demonstrate the superior performances of our MORF method over existing state-of-the-art methods. © 2022, CC BY.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Measuring Sleep Quality from EEG with Machine Learning Approaches

Measuring Sleep Quality from EEG with Machine Learning Appro...

引用

International Joint Conference on Neural Networks

作者： Li-Li Wang Wei-Long Zheng Hai-Wei Ma Bao-Liang Lu Center for Brain-like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center

ISBN: (纸本)9781509006212

This study aims at measuring last-night sleep quality from electroencephalography (EEG). We design a sleep experiment to collect waking EEG signals from eight subjects under three different sleep conditions: 8 hours sleep, 6 hours sleep, and 4 hours sleep. We utilize three machine learning approaches, k-Nearest Neighbor (kNN), support vector machine (SVM), and discriminative graph regularized extreme learning machine (GELM), to classify extracted EEG features of power spectral density (PSD). The accuracies of these three classifiers without feature selection are 36.68%, 48.28%, 62.16%, respectively. By using minimal-redundancy-maximal-relevance (MRMR) algorithm and the brain topography, the classification accuracy of GELM with 9 features is improved largely and increased to 83.57% in average. To investigate critical frequency bands for measuring sleep quality, we examine the features of each band and observe their energy changing. The experimental results indicate that Gamma band is more relevant to measuring sleep quality.

关键词： quality of sleep Electroencephalography Sleep Artificial Intelligence Machine Learning Frequency bands Power spectral density Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Advanced and interpretable corneal staining assessment through fine grained knowledge distillation

引用

npj Digital Medicine 2025年第1期8卷 1-13页

作者： Deng, Yuqing Cheng, Pujin Xu, Ruiwen Ling, Lirong Xue, Hongliang Zhou, Shiyou Huang, Yansong Lyu, Junyan Wang, Zhonghua Wong, Kenneth K. Y. Zhang, Yimin Yu, Kang Zhang, Tingting Hu, Xiaoqing Li, Xiaoyi Tang, Xiaoying Lou, Yan Yuan, Jin State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangzhou China Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Guangdong Provincial Clinical Research Center for Ocular Diseases Guangzhou China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong The Key Laboratory of Advanced Interdisciplinary Studies The First Affiliated Hospital of Guangzhou Medical University Guangzhou China Department of Nutrition School of Public Health Guangzhou Medical University Guangzhou China Queensland Brain Institute The University of Queensland BrisbaneQLD Australia Ophthalmology Pharmaceutical Ltd Guangzhou China Department of Computer School of Intelligent Medicine China Medical University Shenyang China Beijing Institute of Ophthalmology Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University Beijing Key Laboratory of Ophthalmology & Visual Sciences Beijing China

The assessment of corneal fluorescein staining is essential, yet current AI models for Corneal Staining Score (CSS) assessments inadequately identify punctate lesions due to annotation challenges and noise, risk misrepresenting treatment responses through "plateau" effects, and highlight the necessity for real-world evaluations to enhance disease severity assessments. To address these limitations, we developed the Fine-grained Knowledge Distillation Corneal Staining Score (FKD-CSS) model. FKD-CSS integrates fine-grained features into CSS grading, providing continuous and nuanced scores with interpretability. Trained on corneal staining images collected from dry eye (DE) patients across 14 hospitals, FKD-CSS achieved robust accuracy, with a Pearson’s r of 0.898 and an AUC of 0.881 in internal validation, matching senior ophthalmologists’ performance. External tests on 2376 images from 23 hospitals across China further validated its efficacy (r: 0.844–0.899, AUC: 0.804-0.883). Additionally, FKD-CSS demonstrated generalizability in multi-ocular-surface-disease testing, underscoring its potential in handling different staining patterns. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Kinetic and Kinematic Sensors-free Approach for Estimation of Continuous Force and Gesture in sEMG Prosthetic Hands

arXiv

引用

arXiv 2024年

作者： Liu, Gang Wang, Zhenxiang Xi, Chuanmei He, Ziyang Guo, Shanshan Zhang, Rui Yao, Dezhong School of Electrical and information Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain Computer Interface Technology Zhengzhou University Zhengzhou450001 China Engineering Department of International College Zhengzhou University 450001 China School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior Shanghai International Studies University China Clinical Hospital of Chengdu Brain Science Institute MOE Key Laboratory for NeuroInformation University of Electronic Science and Technology of China Chengdu China Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu China

Regression-based sEMG prosthetic hands are widely used for their ability to provide continuous kinetic and kinematic parameters. However, establishing these models requires complex sensors systems to collect corresponding kinetic and kinematic data in synchronization with sEMG, which is cumbersome and user-unfriendly. This paper proposes a kinetic and kinematic sensors-free approach for controlling sEMG prosthetic hands, enabling continuous decoding and execution of three hand movements: individual finger flexion/extension, multiple finger flexion/extension, and fist opening/closing. This approach utilizes only two data points (-1 and 1), representing maximal finger flexion force label and extension force label respectively, and their corresponding sEMG data to establish a near-linear model based on sEMG data and labels. The model's output labels values are used to control the direction and magnitude of fingers forces, enabling the estimation of continuous gestures. To validate this approach, we conducted offline and online experiments using four models: Dendritic Net (DD), Linear Net (LN), Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). The offline analysis assessed each model's ability to classify finger force direction and interpolate intermediate force values, while online experiments evaluated real-time control performance in controlling gestures and accurately adjusting forces. Our results demonstrate that the DD and LN models provide excellent real-time control of finger forces and gestures, highlighting the practical potential of this sensors-free approach for prosthetic applications. This study significantly reduces the complexity of collecting kinetic and kinematic parameters in sEMG-based regression prosthetics, thus enhancing the usability and convenience of prosthetic hands. © 2024, CC BY-NC-SA.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

Effective and efficient multitask learning for brain tumor segmentation

Effective and efficient multitask learning for brain tumor s...

引用

作者： Cheng, Guohua Cheng, Jingliang Luo, Mengyan He, Linyang Tian, Yan Wang, Ruili Institute of Science and Technology for Brain-Inspired Intelligence Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Shanghai200433 China Department of Magnetic Resonance Imaging The First Affiliated Hospital of Zhengzhou University Zhengzhou450052 China Jianpei Technology Co. Ltd Hangzhou310018 China School of Computer and Information Engineering Zhejiang Gongshang University Hangzhou310018 China

Recently, brain tumor segmentation has achieved great success, partially because of deep learning-based relation exploration and multiscale analysis. However, the computational complexity hinders the real-time application. In this paper, we propose a revised multitask learning approach in which a lightweight network with only two scales is adopted to segment different kinds of tumor regions. Moreover, we design a hybrid hard sampling method that considers both sample sparsity and effectiveness. Extensive experiments on the BraTS19 segmentation challenge dataset have shown that our proposed method improves the Dice coefficient by a margin of 0.4–1.0 for different kinds of brain tumor regions and obtains results that are competitive with state-of-the-art brain tumor segmentation approaches. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Enabling Surrogate-Assisted Evolutionary Reinforcement Learning via Policy Embedding 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Tang, Lan Li, Xiaxi Zhang, Jinyuan Li, Guiying Yang, Peng Tang, Ke Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Faculty of Engineering Shenzhen MSU-BIT University Shenzhen518172 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China Department of Statistics and Data Science Southern University of Science and Technology Shenzhen518055 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Evolutionary Reinforcement Learning (ERL) that applying Evolutionary Algorithms (EAs) to optimize the weight parameters of Deep Neural Network (DNN) based policies has been widely regarded as an alternative to traditional reinforcement learning methods. However, the evaluation of the iteratively generated population usually requires a large amount of computational time and can be prohibitively expensive, which may potentially restrict the applicability of ERL. Surrogate is often used to reduce the computational burden of evaluation in EAs. Unfortunately, in ERL, each individual of policy usually represents millions of weights parameters of DNN. This high-dimensional representation of policy has introduced a great challenge to the application of surrogates into ERL to speed up training. This paper proposes a PE-SAERL Framework to at the first time enable surrogate-assisted evolutionary reinforcement learning via policy embedding (PE). Empirical results on 5 Atari games show that the proposed method can perform more efficiently than the four state-of-the-art algorithms. The training process is accelerated up to 7x on tested games, comparing to its counterpart without the surrogate and PE. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：