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  1. Book: Statistical genomics

    Fridley, Brooke / Wang, Xuefeng

    (Methods in molecular biology ; 2629 ; Springer protocols)

    2023  

    Author's details edited by Brooke Fridley and Xuefeng Wang
    Series title Methods in molecular biology ; 2629
    Springer protocols
    Collection
    Keywords Genomics/Statistical methods
    Subject code 572.860727
    Language English
    Size xi, 377 Seiten, Illustrationen, 26 cm
    Publisher Humana Press
    Publishing place New York, NY
    Publishing country United States
    Document type Book
    HBZ-ID HT021828342
    ISBN 978-1-0716-2985-7 ; 9781071629864 ; 1-0716-2985-9 ; 1071629867
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    Zs A 7042 -2629- not available for loan Lesesaal EG

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  2. Book ; Online ; E-Book: Multi-modal EEG monitoring of severely neurologically ill patients

    Wang, Xuefeng / Li, Feng / Pan, Suyue

    2022  

    Title variant Multi-modal EEG-monitoring of severely neurologically ill patients ; Multi modal EEG monitoring of severely neurologically ill patients
    Author's details Xuefeng Wang, Feng Li, Suyue Pan editors
    Keywords Neurology
    Subject code 616.8
    Language English
    Size 1 Online-Ressource (xiii, 360 Seiten), Illustrationen, Diagramme
    Publisher Springer
    Publishing place Singapore
    Publishing country Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT021142413
    ISBN 978-981-16-4493-1 ; 9789811644924 ; 9789811644948 ; 9789811644955 ; 981-16-4493-4 ; 9811644926 ; 9811644942 ; 9811644950
    DOI 10.1007/978-981-16-4493-1
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Book ; Online ; E-Book: Refractory Status Epilepticus

    Wang, Xuefeng / Li, Shichuo

    diagnosis and treatment

    2017  

    Keywords status epilepticus ; epileptic syndrome ; diagnosis ; treatment ; epilepsy
    Subject code 610
    Language English
    Size 1 Online-Ressource (xiii, 331 Seiten), Illustrationen
    Publisher Springer
    Publishing place Singapore
    Publishing country Singapore
    Document type Book ; Online ; E-Book
    Note Lizenzpflichtig
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019477749
    ISBN 978-981-10-5125-8 ; 9789811051241 ; 981-10-5125-9 ; 9811051240
    DOI 10.1007/978-981-10-5125-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Book ; Online: Advances in Steroid-Responsive Encephalopathy

    Tian, Xin / Wang, Xuefeng / Kwan, Patrick

    2020  

    Keywords Medicine ; Neurology & clinical neurophysiology ; steroid-responsive encephalopathy ; mechanism ; diagnosis ; treatment ; prognosis
    Size 1 electronic resource (115 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230631
    ISBN 9782889660421 ; 2889660427
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  5. Article ; Online: Metal (Ni, Pd, and Pt)-Doped BS Monolayers as a Gas Sensor upon Vented Gases in Lithium-Ion Batteries: A First-Principles Study.

    Li, Ming / Wang, Xue-Feng

    Langmuir : the ACS journal of surfaces and colloids

    2024  Volume 40, Issue 6, Page(s) 2969–2978

    Abstract: Real-time monitoring of the vented gases emitted by the thermal runaway of lithium-ion batteries (LIBs) is of great significance to the normal use of LIBs. We study systematically the adsorption and sensing performances of pristine and metal-doped BS ... ...

    Abstract Real-time monitoring of the vented gases emitted by the thermal runaway of lithium-ion batteries (LIBs) is of great significance to the normal use of LIBs. We study systematically the adsorption and sensing performances of pristine and metal-doped BS monolayers to five typical gases (CO, CO
    Language English
    Publishing date 2024-02-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021/acs.langmuir.3c03088
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Bilateral coronary artery aneurysms with chronic total occlusion of the proximal left anterior descending coronary artery and apical aneurysm in a 32-year-old man.

    Hu, Yuanmin / Wang, Xuefeng

    Coronary artery disease

    2023  Volume 34, Issue 8, Page(s) 614–616

    MeSH term(s) Male ; Humans ; Adult ; Coronary Vessels/diagnostic imaging ; Coronary Vessels/surgery ; Coronary Aneurysm/diagnostic imaging ; Coronary Aneurysm/surgery ; Vascular Diseases ; Coronary Angiography
    Language English
    Publishing date 2023-10-03
    Publishing country England
    Document type Case Reports ; Journal Article
    ZDB-ID 1047268-x
    ISSN 1473-5830 ; 0954-6928
    ISSN (online) 1473-5830
    ISSN 0954-6928
    DOI 10.1097/MCA.0000000000001297
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3039: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article: Electronic and Spintronic Properties of Armchair MoSi

    Su, Xiao-Qian / Wang, Xue-Feng

    Nanomaterials (Basel, Switzerland)

    2023  Volume 13, Issue 4

    Abstract: Structural and physical properties of armchair ... ...

    Abstract Structural and physical properties of armchair MoSi
    Language English
    Publishing date 2023-02-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662255-5
    ISSN 2079-4991
    ISSN 2079-4991
    DOI 10.3390/nano13040676
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Multi-omics Data Deconvolution and Integration: New Methods, Insights, and Translational Implications.

    Wang, Xuefeng / Fridley, Brooke L

    Methods in molecular biology (Clifton, N.J.)

    2023  Volume 2629, Page(s) 1–9

    Abstract: In the current era of multi-omics, new sequencing and molecular profiling technologies have facilitated our quest for a deeper and broader understanding of the variations and dynamic regulations in human genomes. However, analyzing and integrating data ... ...

    Abstract In the current era of multi-omics, new sequencing and molecular profiling technologies have facilitated our quest for a deeper and broader understanding of the variations and dynamic regulations in human genomes. However, analyzing and integrating data generated from diverse platforms, modalities, and large-scale heterogeneous samples to extract functional and clinically valuable information remains a significant challenge. Here, we first discuss recent advances in methods and algorithms for analyzing data at the genome, transcriptome, proteome, metabolome, and microbiome levels, followed by emerging methods for leveraging single-cell sequencing and spatial transcriptomic data. We also highlight the mechanistic insights that these advances can bring to the field, as well as the current challenges and outlooks relating to their translational and reproducible adoption at the population level. It is evident that novel statistical methods, which were inspired by new assays, will enable the associated molecular profiling pipelines and experimental designs to continuously improve our understanding of the human genome and the downstream consequences in the transcriptome, epigenome, proteome, metabolome, regulome, and microbiome.
    MeSH term(s) Humans ; Proteome/genetics ; Multiomics ; Proteomics ; Gene Expression Profiling/methods ; Transcriptome ; Genome, Human
    Chemical Substances Proteome
    Language English
    Publishing date 2023-03-16
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-2986-4_1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.

    Yao, Sijie / Wang, Xuefeng

    Methods in molecular biology (Clifton, N.J.)

    2023  Volume 2629, Page(s) 11–21

    Abstract: Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omics ... ...

    Abstract Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omics datasets, statistical methods such as the least absolute shrinkage and selection operator (Lasso) have been widely applied for cancer biomarker discovery. Due to their scalability and demonstrated prediction performance, machine learning methods such as XGBoost and neural network models have also been gaining popularity in the community recently. However, compared to more traditional survival methods such as Kaplan-Meier and Cox regression methods, high-dimensional methods for survival outcomes are still less well known to biomedical researchers. In this chapter, we will discuss the key analytical procedures in employing these methods for identifying biomarkers associated with survival data. We will also identify important considerations that emerged from the analysis of actual omics data. Some typical instances of misapplication and misinterpretation of machine learning methods will also be discussed. Using lung cancer and head and neck cancer datasets as demonstrations, we provide step-by-step instructions and sample R codes for prioritizing prognostic biomarkers.
    MeSH term(s) Survival Analysis ; Prognosis ; Machine Learning ; Biomarkers ; Datasets as Topic ; Neural Networks, Computer ; Kaplan-Meier Estimate ; Proportional Hazards Models ; Lung Neoplasms/diagnosis ; Lung Neoplasms/metabolism ; Head and Neck Neoplasms/diagnosis ; Head and Neck Neoplasms/metabolism ; Programming Languages ; Deep Learning ; Biomarkers, Tumor ; Humans ; Male ; Female
    Chemical Substances Biomarkers ; Biomarkers, Tumor
    Language English
    Publishing date 2023-03-16
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-2986-4_2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Action recognition for sports combined training based on wearable sensor technology and SVM prediction.

    Liu, Zhewei / Wang, Xuefeng

    Preventive medicine

    2023  Volume 173, Page(s) 107582

    Abstract: In the field of sports, coaches have mainly relied on observing the performance of athletes on the spot to formulate suitable training plans for athletes, which has extremely high requirements for the professionalism of coaches. Based on the above ... ...

    Abstract In the field of sports, coaches have mainly relied on observing the performance of athletes on the spot to formulate suitable training plans for athletes, which has extremely high requirements for the professionalism of coaches. Based on the above requirements, this paper designs a sports action recognition system for sports enthusiasts based on the SVM algorithm optimization model, and for the purpose of verifying the applicability of the system to different sports fields, experiments are carried out on basketball actions and race walking actions. The system uses wearable sensors to capture the motion data of the user, and then analyzes and identifies the user's actions through the SVM algorithm optimization model. By standardizing the user's sports combination training under the system algorithm, the user can improve their training efficiency and reduce the risk of injury. To establish the human body motion model, this paper divides the human skeleton model into five motion branches. The rotation freedom constraints and joint rotation angle range limits are added to the model to ensure the accuracy of the motion analysis. Combining the forward kinematics of the robot and the homogeneous coordinate transformation, the human body joint rotation motion model and the human bone position and posture model are established. In the end, the user can standardize the sports combination training under the system algorithm. In this paper, through the research of wearable sensor technology and sports combined training action recognition, and apply it to practical life, it aims to promote its development and application.
    MeSH term(s) Humans ; Support Vector Machine ; Sports ; Wearable Electronic Devices ; Walking ; Technology
    Language English
    Publishing date 2023-06-20
    Publishing country United States
    Document type Journal Article
    ZDB-ID 184600-0
    ISSN 1096-0260 ; 0091-7435
    ISSN (online) 1096-0260
    ISSN 0091-7435
    DOI 10.1016/j.ypmed.2023.107582
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 878: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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