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7th International Conference on Computer Information Science and Application technology, CISAT 2024

作者： Chen, Zhongtao Tian, Mengxin Tang, Zhaoqing Wang, Xuefei Yu, Jinhua Fudan University Biomedical Engineering Center School of Information Science and Technology Shanghai China Fudan University Zhongshan Hospital Department of Gastrointestinal Surgery Shanghai China

ISBN: (纸本)9798350375107

Gastric cancer has been one of the leading causes of death among oncological patients. Lymph node (LN) metastasis classification is an important task for computer-aided diagnosis (CAD) using abdominal CT images. Due to the size and shape variation of gastric tumor, it is challenging to propose a reliable solution. In this paper, we develop an improved classification model called double stream mask guided attention network (DSMANet), which can fuse features from tumor region and gastric region. Meanwhile, we innovatively devise iterative softpool attentional feature fusion (iSAFF) block instead of the simple feature concatenate. We evaluate our DSMANet on a self-collected CT images dataset containing 649 cases. Our comparison experiment and ablation experiment demonstrate that the proposed method achieves favorable classification performance compared with the SOTA classification model. © 2024 IEEE.

关键词： Computerized tomography

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Revolutionizing Autism Spectrum Disorder Diagnosis: Harnessing the Power of Machine Learning and MRI for Enhanced Neurodevelopmental Care 2

Revolutionizing Autism Spectrum Disorder Diagnosis: Harnessi...

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Krishna Kumar, R. Muthuramalingam, Akila Shankar Iyer, Rajesh Satwika, S.R. Vanithashree, P. Ahamed Sherief, M.F. Sathiya Priya, N. K. S. Rangasamy College of Technology Department of Information Technology Tiruchengode India KPR Institute of Engineering and Technology Department of Biomedical Engineering Coimbatore India Kovai Medical Center and Hospital Consultant Neurologist and Epileptologist Coimbatore India

ISBN: (纸本)9798350349221

A complex neurodevelopmental disorder, Autism Spectrum Disorder (ASD) is characterized by restricted and repetitive activities as well as difficulties with social interaction. According to statistical reports taken on 2023, about one in 36 children are now diagnosed with autism worldwide [16]. Early detection and intervention significantly improve their social and personal life, even though effective therapies for ASD are still elusive. In the proposed work, an artificial intelligence (AI)-based novel method for early autism identification is presented. The technique examines patterns in MRI images using various ML algorithms. ABIDE website provides MRI image datasets for the work. A specialized website that allows users to upload their MRI images for autism diagnosis has been built by utilizing this AI-based method. An accuracy of 92% emphasizes the system's potential as a trustworthy technique for early ASD detection. By strengthening early intervention techniques and enhancing overall ASD treatment outcomes, the innovative technique would represent significant *** Relevance - This work provides significant parameter to diagnosis and treat ASD by the Neurosurgeons and the accuracy of ASD detection would be 95%. © 2024 IEEE.

关键词： Websites

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Plasma-Enabled Graphene Quantum Dot Hydrogel-Magnesium Composites as Bioactive Scaffolds for In Vivo Bone Defect Repair

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ACS Applied Materials and Interfaces 2023年第38期15卷 44607-44620页

作者： Wong, Pei-Chun Kurniawan, Darwin Wu, Jia-Lin Wang, Wei-Ru Chen, Kuan-Hao Chen, Chieh-Ying Chen, Ying-Chun Veeramuthu, Loganathan Kuo, Chi-Ching Ostrikov, Kostya Ken Chiang, Wei-Hung Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei110 Taiwan Orthopedics Research Center Taipei Medical University Hospital Taipei110 Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Orthopedics School of Medicine College of Medicine Taipei Medical University Taipei110 Taiwan Department of Orthopedics Taipei Medical University Hospital Taipei110 Taiwan Centers for Regional Anesthesia and Pain Medicine Wan Fang Hospital Taipei Medical University Taipei110 Taiwan School of Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei110 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei110 Taiwan Department of Orthopedics Shuang Ho Hospital Taipei Medical University New Taipei235 Taiwan Department of Mechanical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Molecular Science and Engineering Institute of Organic and Polymeric Materials National Taipei University of Technology Taipei106 Taiwan BrisbaneQLD4000 Australia

Bioactive and mechanically stable metal-based scaffolds are commonly used for bone defect repair. However, conventional metal-based scaffolds induce nonuniform cell growth, limiting damaged tissue restoration. Here, we develop a plasma nanotechnology-enhanced graphene quantum dot (GQD) hydrogel-magnesium (Mg) composite scaffold for functional bone defect repair by integrating a bioresource-derived nitrogen-doped GQD (NGQD) hydrogel into the Mg ZK60 alloy. Each scaffold component brings major synergistic advantages over the current alloy-based state of the art, including (1) mechanical support of the cortical bone and calcium deposition by the released Mg2+ during degradation;(2) enhanced uptake, migration, and distribution of osteoblasts by the porous hydrogel;and (3) improved osteoblast adhesion and proliferation, osteogenesis, and mineralization by the NGQDs in the hydrogel. Through an in vivo study, the hybrid scaffold with the much enhanced osteogenic ability induced by the above synergy promotes a more rapid, uniform, and directional bone growth across the hydrogel channel, compared with the control Mg-based scaffold. This work provides insights into the design of multifunctional hybrid scaffolds, which can be applied in other areas well beyond the demonstrated bone defect repair. © 2023 American Chemical Society.

关键词： Semiconductor quantum dots

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A biogenesis construction of CuO@MWCNT via Chenopodium album extract: an effective electrocatalyst for synaptic plasticity neurodegenerative drug pollutant detection

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Environmental Science and Pollution Research 2023年第33期30卷 79744-79757页

作者： Pandiyarajan, Sabarison Velayutham, Gurunathan Liao, Ai-Ho Manickaraj, Shobana Sebastin Mary Ramachandran, Balaji Lee, Kuo-Yu Chuang, Ho-Chiao Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Mechanical Engineering National Taipei University of Technology Taipei Taiwan PG & Research Department of Chemistry Bishop Heber College Tamil Nadu Tiruchirappalli India Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan SV Probe Technology Taiwan Co. Ltd Taipei10453 Taiwan

Clioquinol (CLQ) is one of the most toxic halogenated neurodegenerative drugs, and its synaptic plasticity effect directly affects human health and the environment. Cupric oxide (CuO) is an ideal electrocatalyst owing to its earth-abundance, non-toxic nature, and cost-effectiveness. Since phenolate oxygen and pyridine nitrogen in CLQ act as an electron donor and pave the way for detection with Cu2+ ions in the CuO. Designing the architecture of CuO with a multi-walled carbon nanotube (MWCNT) is a sensible strategy to improve the electrochemical activity of the developed sensor. Inspired by the bio-synthesis and green processing, we have demonstrated the in-situ synthesis of CuO nanosphere-decorated MWCNT by Chenopodium album leaf extract through a sonochemical approach and explored its electrochemical sensing performance toward CLQ. The physical comprehensive characterization of prepared nanocomposite was investigated by various microscopic and spectroscopic techniques. For comparison studies, the CuO nanosphere was prepared by the same preparation process without MWCNT. Based on the physical characterization outcomes, the morphological nature of CuO was observed to be a sphere-like structure, which was decorated on the MWCNT with an average crystallite size of 16 nm (± 1 nm). Based on the electrochemical studies, the fabricated nanocomposite exhibits a wider linear range of 0.025–1375 μM, with a minimum detection limit of 4.59 nM L–1 toward CLQ. The viability examination on the biological matrix obtained considerable spike recoveries. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Nanospheres

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Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics 38

Probabilistic Decomposed Linear Dynamical Systems for Robust...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Yenho Mudrik, Noga Johnsen, Kyle A. Alagapan, Sankaraleengam Charles, Adam S. Rozell, Christopher J. Machine Learning Center Georgia Institute of Technology United States School of Electrical and Computer Engineering Georgia Institute of Technology United States Coulter Dept. of Biomedical Engineering Emory University Georgia Institute of Technology United States Department of Biomedical Engineering Mathematical Institute for Data Science Center for Imaging Science Kavli Neuroscience Discovery Institute Johns Hopkins University United States

Time-varying linear state-space models are powerful tools for obtaining mathematically interpretable representations of neural signals. For example, switching and decomposed models describe complex systems using latent variables that evolve according to simple locally linear dynamics. However, existing methods for latent variable estimation are not robust to dynamical noise and system nonlinearity due to noise-sensitive inference procedures and limited model formulations. This can lead to inconsistent results on signals with similar dynamics, limiting the model's ability to provide scientific insight. In this work, we address these limitations and propose a probabilistic approach to latent variable estimation in decomposed models that improves robustness against dynamical noise. Additionally, we introduce an extended latent dynamics model to improve robustness against system nonlinearities. We evaluate our approach on several synthetic dynamical systems, including an empirically-derived brain-computer interface experiment, and demonstrate more accurate latent variable inference in nonlinear systems with diverse noise conditions. Furthermore, we apply our method to a real-world clinical neurophysiology dataset, illustrating the ability to identify interpretable and coherent structure where previous models cannot. © 2024 Neural information processing systems foundation. All rights reserved.

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Liver Tumor Decision Support System on Human Magnetic Resonance Images:A Comparative Study

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Computer Systems Science & engineering 2023年第8期46卷 1653-1671页

作者： Hiam Alquran Yazan Al-Issa Mohammed Alslatie Isam Abu-Qasmieh Amin Alqudah Wan Azani Mustafa Yasmin Mohd Yacob Department of Biomedical Systems and Informatics Engineering Yarmouk University 556Irbid21163Jordan Department of Biomedical Engineering Jordan University of Science and TechnologyIrbid22110Jordan Department of Computer Engineering Yarmouk University 556Irbid21163Jordan The of Biomedical Technology King Hussein Medical CenterRoyal Jordanian Medical ServiceAmman11855Jordan Faculty of Electrical Engineering&Technology Campus Pauh PutraUniversiti Malaysia PerlisArau02600PerlisMalaysia Faculty of Electronic Engineering&Technology Campus Pauh PutraUniversiti Malaysia PerlisArau02600PerlisMalaysia Advanced Computing Centre of Excellence(CoE)Universiti Malaysia PerlisArau02600PerlisMalaysia

Liver cancer is the second leading cause of cancer death *** tumor detection may help identify suitable treatment and increase the survival *** imaging is a non-invasive tool that can help uncover abnormalities in human *** Resonance Imaging(MRI),in particular,uses magnetic fields and radio waves to differentiate internal human organs ***,the interpretation of medical images requires the subjective expertise of a radiologist and ***,building an automated diagnosis computer-based system can help specialists reduce incorrect *** paper proposes a hybrid automated system to compare the performance of 3D features and 2D features in classifying magnetic resonance liver tumor *** paper proposed two models;the first one employed the 3D features while the second exploited the 2D *** first system uses 3D texture attributes,3D shape features,and 3D graphical deep descriptors beside an ensemble classifier to differentiate between four 3D tumor *** top of that,the proposed method is applied to 2D slices for comparison *** proposed approach attained 100%accuracy in discriminating between all types of tumors,100%Area Under the Curve(AUC),100%sensitivity,and 100%specificity and precision as well in 3D liver *** the other hand,the performance is lower in 2D *** maximum accuracy reached 96.4%for two classes and 92.1%for four *** top-class performance of the proposed system can be attributed to the exploitation of various types of feature selection methods besides utilizing the ReliefF features selection technique to choose the most relevant features associated with different *** novelty of this work appeared in building a highly accurate system under specific circumstances without any processing for the images and human input,besides comparing the performance between 2D and 3D *** the future,the presented work can be extended to be

关键词： Liver tumors ensemble classifier 3D shape features 3D cooccurrence matrix ResNet101

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Self-sensing intelligent microrobots for noninvasive and wireless monitoring systems

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Microsystems & Nanoengineering 2023年第4期9卷 233-245页

作者： Zhongyi Li Kun Wang Chaojian Hou Chunyang Li Fanqing Zhang Wu Ren Lixin Dong Jing Zhao School of Mechatronical Engineering Beijing Institute of Technology100081 BeijingChina Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology100081 BeijingChina Department of Biomedical Engineering City University of Hong Kong999077 Kowloon TongHong KongChina School of Integrated Circuits and Electronics Beijing Institute of Technology100081 BeijingChina

Microrobots have garnered tremendous attention due to their small size,flexible movement,and potential for various in situ ***,functional modification of microrobots has become crucial for their interaction with the environment,except for precise motion ***,a novel artificial intelligence(AI)microrobot is designed that can respond to changes in the external environment without an onboard energy supply and transmit signals wirelessly in real *** AI microrobot can cooperate with external electromagnetic imaging equipment and enhance the local radiofrequency(RF)magnetic field to achieve a large penetration sensing depth and a high spatial *** working ranges are determined by the structure of the sensor circuit,and the corresponding enhancement effect can be modulated by the conductivity and permittivity of the surrounding environment,reaching~560 times at *** the control of an external magnetic field,the magnetic tail can actuate the microrobotic agent to move accurately,with great potential to realize in situ monitoring in different places in the human body,almost noninvasively,especially around potential diseases,which is of great significance for early disease discovery and accurate *** addition,the compatible fabrication process can produce swarms of functional *** findings highlight the feasibility of the self-sensing AI microrobots for the development of in situ diagnosis or even treatment according to sensing signals.

关键词： treatment precise conductivity

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Inflammation and Microbiota Regulation Potentiate Pneumonia Therapy by Biomimetic Bacteria and Macrophage Membrane Nanosystem

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Research 2023年第4期2023卷 399-413页

作者： Yuan Li Xiangmei Liu Zhenduo Cui Yufeng Zheng Hui Jiang Yu Zhang Zhaoyang Li Shengli Zhu Paul K Chu Shuilin Wu School of Materials Science and Engineering Peking UniversityBeijing 100871China The Key Laboratory of Advanced Ceramics and Machining Technology by the Ministry of Education of China School of Materials Science and EngineeringTianjin UniversityTianjin 300072China Biomedical Materials Engineering Research Center Hubei Key Laboratory of Polymer MaterialsMinistry-of-Education Key Laboratory for the Green Preparation and Application of Functional MaterialsSchool of Materials Science and EngineeringHubei UniversityWuhan430062China School of Health Science and Biomedical Engineering Hebei University of TechnologyXiping Avenue 5340Beichen DistrictTianjin 300401China Department of Orthopedics Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou510080China Department of Physics Department of Materials Science and Engineeringand Department of Biomedical EngineeringCity University of Hong KongKowloon 999077Hong KongChina.

While conventional nanosystems can target infected lung tissue,they cannot achieve precise cellular targeting and enhanced therapy by modulating inflammation and microbiota for effective ***,we designed a nucleus-targeted nanosystem with adenosine triphosphate(ATP)and reactive oxygen species stimuli-response to treat pneumonia coinfected with bacteria and virus that is enhanced through inflammation and microbiota *** nucleus-targeted biomimetic nanosystem was prepared through the combined bacteria-macrophage membrane and loaded hypericin and ATP-responsive dibenzyl oxalate(MMHP)*** MMHP despoiled the Mg^(2+)of intracellular cytoplasm in bacteria to achieve an effective bactericidal ***,MMHP can target the cell nucleus and inhibit the H1N1 virus duplication by inhibiting the activity of *** possessed an immunomodulatory ability to reduce the inflammatory response and activate CD8^(+)T cells for assisted infection *** the mice model,the MMHP effectively treated pneumonia coinfected with Staphylococcus aureus and H1N1 ***,MMHP mediated the composition of gut microbiota to enhance the pneumonia ***,the dual stimuli-responsive MMHP possessed promising clinical translational potential to therapy infectious pneumonia.

关键词： inflammation H1N1 lung

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Acceptor engineering Produces Ultrafast Nonradiative Decay in NIR-Ⅱ Aza-BODIPY Nanoparticles for Efficient Osteosarcoma Photothermal Therapy via Concurrent Apoptosis and Pyroptosis

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Research 2024年第1期2023卷 625-635页

作者： Zhenxiong Shi Hua Bai Jiaxing Wu Xiaofei Miao Jia Gao Xianning Xu Yi Liu Jiamin Jiang Jiaqi Yang Jiaxin Zhang Tao Shao Bo Peng Huili Ma Dan Zhu Guojing Chen Wenbo Hu Lin Li Wei Huang Frontiers Science Center for Flexible Electronics Xi’an Institute of Flexible Electronics(IFE)and Xi’an Institute of Biomedical Materials&EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Key Laboratory for Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Nanjing University of Posts&TelecommunicationsNanjing 210023China Key Laboratory of Flexible Electronics(KLOFE)and IAM Nanjing Tech UniversityNanjing 211800China Britton Chance Center for Biomedical Photonics-MoE Key Laboratory for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Advanced Biomedical Imaging FacilityHuazhong University of Science and TechnologyWuhan 430074China Department of Orthopedics Xijing HospitalThe Fourth Military Medical UniversityXi’an 710032China The Institute of Flexible Electronics(IFE Future Technologies)Xiamen UniversityXiamen 361005China

Small-molecule photothermal agents(PTAs)with intense second near-infrared(NIR-Ⅱ,1,000 to 1,700 nm)absorption and high photothermal conversion efficiencies(PCEs)are promising candidates for treating deep-seated tumors such as *** date,the development of small-molecule NIR-Ⅱ PTAs has largely relied on fabricating donor–acceptor–donor(D–A–D/D′)structures and limited success has been ***,through acceptor engineering,a donor–acceptor–acceptor(D–A–A′)-structured NIR-Ⅱ aza-boron-dipyrromethene(aza-BODIPY)PTA(SW8)was readily developed for the 1,064-nm laser-mediated phototheranostic treatment of *** the donor groups to acceptor groups produced remarkable red-shifts of absorption maximums from first near-infrared(NIR-Ⅰ)regions(~808 nm)to NIR-Ⅱ ones(~1,064 nm)for aza-BODIPYs(SW1 to SW8).Furthermore,SW8 self-assembled into nanoparticles(SW8@NPs)with intense NIR-Ⅱ absorption and an ultrahigh PCE(75%,1,064 nm).This ultrahigh PCE primarily originated from an additional nonradiative decay pathway,which showed a 100-fold enhanced decay rate compared to that shown by conventional pathways such as internal conversion and vibrational ***,SW8@NPs performed highly efficient 1,064-nm laser-mediated NIR-Ⅱ photothermal therapy of osteosarcoma via concurrent apoptosis and *** work not only illustrates a remote approach for treating deep-seated tumors with high spatiotemporal control but also provides a new strategy for building high-performance small-molecule NIR-Ⅱ PTAs.

关键词： donor BODIPY intense

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Modeling of Thermal Processes in a Microcontroller System with the Use of Hybrid, Fractional Order Transfer Functions 21st

Modeling of Thermal Processes in a Microcontroller System wi...

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21st Polish Control Conference, PCC 2023

作者： Oprzedkiewicz, Krzysztof Rosol, Maciej Mitkowski, Wojciech Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031351693

In the paper the problem of modeling of thermal processes in microcontroller system is addressed. The proposed models allow to describe thermal processes during work of an evaluation system. The temperature in critical places of the system is measured using thermal camera. The proposed models have the form of hybrid transfer functions, containing both Integer Order (IO) and Fractional Order (FO) parts. The step responses of the proposed transfer functions are computed analytically. Results of experiments show that the proposed models are more accurate in the sense of Mean Square Error (MSE) cost function than typical transfer function models with delay. The proposed models can be applied to predict of overheating of microcotroller systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Microcontrollers

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