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Machine learning applications in healthcare clinical practice and research

World Journal of Clinical Cases 2025年第1期13卷 16-21页

作者： Nikolaos-Achilleas Arkoudis Stavros P Papadakos Research Unit of Radiology and Medical Imaging School of MedicineNational and Kapodistrian University of AthensAthens 11528Greece 2^(nd)Department of Radiology “Attikon”General University HospitalMedical SchoolNational and Kapodistrian University of AthensChaidari 12462Greece Department of Gastroenterology Laiko General HospitalNational and Kapodistrian University of AthensAthens 11527Greece

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human *** its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and *** this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical *** authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and *** addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+***,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

关键词： Machine Learning Artificial Intelligence Clinical Practice Research Glomerular filtration rate Non-alcoholic fatty liver disease Medicine

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Carcinosarcoma of the breast:Facing the challenge of a rare nosologic entity

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World Journal of Clinical Cases 2025年第2期13卷 14-20页

作者： Aikaterini Mastoraki Maria Tsamopoulou Foivos-Konstantinos Stamatis Alexios Strimpakos Ero Mouchtouri Christiana Panagi Evgenia Mela Sotiria Mastoraki Aristotelis Kechagias Dimitrios Schizas Department of Surgery National and Kapodistrian University of AthensLaikon General HospitalAthens 11527Greece Department of Surgery National and Kapodistrian University of AthensAthens 11527Greece Department of Medical Oncology Hygeia HospitalAthens 15123Greece Department of Radiology Henry Dunant Hospital CenterAthens 11526Greece Department of Surgery Athens Metropolitan HospitalAthens 15562Greece

Carcinosarcoma(CS),also known as metaplastic breast carcinoma with mesenchymal differentiation,is one of the five distinct subtypes of metaplastic breast *** is considered as a mixed,biphasic neoplasm consisting of a carcinomatous component combined with a malignant nonepithelial element of mesenchymal origin without an intermediate transition *** cellular origin of this neoplasm remains controversial,most researchers declare that neoplastic cells derive from a cellular structure with potential biphasic *** recent research on the therapeutic strategies against CS neoplastic disorders,surgical resection appears the only potentially curative *** CS metastasize by the lymphatic route,axillary assessment with sentinel lymph node biopsy and/or axillary lymph node dissection is always ***,the tumor also presents a hematogenous metastatic pattern including pleural,pulmonary,liver,brain and less commonly bone ***,surgical removal of breast CS does not necessarily ensure patient’s long-term ***,alternative therapies,such as radio-and chemotherapy proved insufficient and 5-year survival rate is ***,there is evidence that following surgery,the combination of radio and chemotherapy is associated with a better prognosis than either treatment *** aim of this review is to evaluate the results of surgical treatment for breast CS with special reference to the extent of its histological *** features,histogenesis,morphological and immunochemical findings are discussed,while the role of current diagnostic and therapeutic management of this aggressive neoplasm is emphasized.

关键词： Carcinosarcoma Breast Diagnostic approach Therapeutic management Prognostic parameters

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Enhanced solid-electrolyte interface efficiency for practically viable hydrogen-air fuel cell systems

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Journal of Energy Chemistry 2025年第1期100卷 356-368页

作者： Venkitesan Sakthivel Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering (BK21 FOUR) Hydrogen and Fuel Cell Research Center Jeonbuk National University Jeonju Department of Life Science Jeonbuk National University

Proton exchange membrane fuel cells （PEMFCs） provide an appealing sustainable energy system,with the solid-electrolyte membrane playing a crucial role in its overall ***,sulfonated poly（1,4-phenylene ether-ether sulfone）(SPEES),an aromatic hydrocarbon polymer,has garnered considerable attention as an alternative to Nafion ***,the long-term durability and stability of SPEES present a significant *** this context,we introduce a potential solution in the form of an additive,specifically a core–shell-based amine-functionalized iron titanate （A–Fe2TiO5）,which holds promise for improving the lifetime,proton conductivity,and power density of SPEES in *** modified SPEES/A–Fe2TiO5composite membranes exhibited notable characteristics,including high water uptake,enhanced thermomechanical stability,and oxidative ***,the SPEES membrane loaded with 1.2 wt%of A–Fe2TiO5demonstrates a maximum proton conductivity of 155 mS cm-1,a twofold increase compared to the SPEES membrane,at 80°C under 100%relative humidity （RH）.Furthermore,the 1.2 wt%of A–Fe2TiO5/SPEES composite membranes exhibited a maximum power density of 397.37 mW cm-2and a current density of 1148 mA cm-2at 60°C under 100%RH,with an opencircuit voltage decay of 0.05 m V/h during 103 h of continuous *** study offers significant insights into the development and understanding of innovative SPEES nanocomposite membranes for PEMFC applications.

关键词： Acid-base Hybrid membrane Proton conductivity Polymer electrolyte fuel cell Single-cell performance

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Apolipoprotein E elicits targetdirected miRNA degradation to maintain neuronal integrity

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Neural Regeneration Research 2025年第9期20卷 2577-2578页

作者： Jiazi Tan Chin-Tong Ong Temasek Life Sciences Laboratory National University of SingaporeSingapore Department of Biological Sciences National University of SingaporeSingapore

Apolipoprotein E has diverse functions in neurons:Apolipoprotein E(ApoE)is a glycoprotein that primarily regulates lipid metabolism and transport in the central nervous *** are three predominant human ApoE protein isoforms with cysteine and arginine substitutions at amino acid positions 112 and 158 that impact their lipidation and related functions(Flowers and Rebeck,2020).ApoE2 is characterized by Cys112 and Cys158,ApoE3 by Cys112 and Arg158,whereas ApoE4 contains Arg112 and Arg158.

关键词： metabolism glycoprotein maintain

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Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 231-250页

作者： Tajmal Hussain Jongwon Seok Department of Information and Communication Engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product *** light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing *** this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual *** evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different *** ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted *** evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and *** analysis with recent studies also showed the superior performance of our methodology.

关键词： Smart manufacturing CNN steel defects ensemble models

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Recovery of the injured neural system through gene delivery to surviving neurons in Parkinson’s disease

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Neural Regeneration Research 2025年第10期20卷 2855-2861页

作者： Chanchal Sharma Sehwan Kim Hyemi Eo Sang Ryong Kim School of Life Science Kyungpook National UniversityDaeguKorea BK21 FOUR KNU Creative BioResearch Group Kyungpook national university DaeguKorea Brain Science and Engineering Institute Kyungpook National UniversityDaeguKorea

A critical unaddressed problem in Parkinson’s disease is the lack of therapy that slows or hampers *** medications effectively manage symptoms,they offer no long-term benefit because they fail to address the underlying neuronal *** highlights that the elusive goals of halting progression and restoring damaged neurons limit the long-term impact of current *** clinical trials using gene therapy have demonstrated the safety of various vector delivery systems,dosages,and transgenes expressed in the central nervous system,signifying tangible and substantial progress in applying gene therapy as a promising Parkinson’s disease ***,at diagnosis,many dopamine neurons remain in the substantia nigra,offering a potential window for recovery and *** propose that modulating these surviving dopamine neurons and axons in the substantia nigra and striatum using gene therapy offers a potentially more impactful therapeutic approach for future ***,innovative gene therapies that focus on preserving the remaining elements may have significant potential for enhancing long-term outcomes and the quality of life for patients with Parkinson’s *** this review,we provide a perspective on how gene therapy can protect vulnerable elements in the substantia nigra and striatum,offering a novel approach to addressing Parkinson’s disease at its core.

关键词： adeno-associated virus gene therapy neuroprotection neurorestoration neurotrophic factor nigrostriatal dopamine pathway pro-survival protein

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Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao Ren Cheng Xu Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

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Local magnetic moment oscillation around an Anderson impurity on graphene

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 192-201页

作者： Shuai Li Zhen Ma Jin-Hua Gao School of Science Hebei University of Science and Technology School of Electronics and Information Zhengzhou University of Light Industry School of Physics and Wuhan national High Magnetic Field Center Huazhong University of Science and Technology

We theoretically investigate the spin resolved Friedel oscillation （FO） and quasiparticle interference （QPI） in graphene induced by an Anderson *** the impurity becomes magnetic,the resulted FO becomes spin dependent,which gives rise to a local magnetic moment oscillation with an envelop decaying as r-2in real space in the doping ***,at half filling,the electron density and local magnetic moment will not oscillate but decay as *** spin resolved FO has both sublattice and spin ***,the local magnetic moment decay at half filling only occurs at one sublattice of graphene,which is quite like the phenomenon observed in the STM experiment (***ález-Herrero et al.,Science 352,437 （2016）).We further give an analytic formula about such spin dependent FO based on the stationary phase ***,we study the interference of quasiparticles around the magnetic impurity by calculating the spin dependent Fourier-transformed local density of states （FT-LDOS）.Our work gives a comprehensive understanding about the local magnetic moment oscillation around an Anderson impurity on graphene.

关键词： Friedel oscillation local magnetic moment graphene Anderson impurity

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Synergistic promotion strategy of “dual-site” and “dual-path” to enhance the C–C coupling between CO2 and HCHO driven by photoelectrocatalysis

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Journal of Energy Chemistry 2025年第1期100卷 39-49页

作者： Hongqiang Yang Jianfeng Zheng Guoyu Wang Yifei Gao Yatao Yang Jia Li Xiaojin Han Yan Cui Zhanggen Huang national Key Laboratory of High Efficiency and Low Carbon Utilization of Coal Institute of Coal Chemistry Chinese Academy of Science university of Chinese Academy of Science Shenyang university of Chemical Technology

Photoelectrocatalytic coupling CO2and volatile organic compounds （VOCs） is a promising green strategy for the synergistic conversion of the two carbon-containing resources to *** catalytic efficiency is always at the mercy of chemical inertness of CO2and the competitive hydrogen evolution of ***,a modified g-C3N4/ZnAl-LDH Z-scheme heterojunction catalyst with dual reaction site was rationally designed and precisely *** Faraday efficiency of ethanol reached 68.67%with a corresponding formation rate of 227.3μmol *** revealed by in-situ characterizations and density functional theory calculations,CO2and HCHO were absorbed at Zn site and N site,***,*CO generated from CO2and HCHO was converted to*CH3O and*CHO on the dual-active-site *** detailed reaction mechanism experiments indicated that C–C coupling only occurred between*CO and*CH3O in electrocatalysis *** from the“*CO+*CH3O”path,another“*CO+*CHO”coupling path was also detected in photoelectrocatalytic *** selectivity of ethanol was significantly enhanced due to the synthesis of dual-site catalyst and the dual-path coupling path between CO2and HCHO simultaneously driven by light and electricity.

关键词： Photoelectrocatalysis Z-scheme C–C coupling Ethanol

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

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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

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