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  1. Book ; Online ; E-Book: Artificial intelligence in radiation oncology and biomedical physics

    Valdes, Gilmer / Xing, Lei

    (Imaging in Medical Diagnosis and Therapy Series)

    2023  

    Abstract: Artificial Intelligence in Radiation Oncology and Biomedical Physics explores how modern machine learning and other AI techniques impact millions of global cancer patients. This pioneering book includes contributions from researchers and clinicians from ...

    Author's details edited by Gilmer Valdes and Lei Xing
    Series title Imaging in Medical Diagnosis and Therapy Series
    Abstract "Artificial Intelligence in Radiation Oncology and Biomedical Physics explores how modern machine learning and other AI techniques impact millions of global cancer patients. This pioneering book includes contributions from researchers and clinicians from around the world. Its focus is on the clinical applications of machine learning for medical physics, particularly in radiomics, segmentation, treatment planning, quality assurance, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is envisioned. This book will be an essential companion to radiation oncologists, medical physicists, and medical dosimetrists"--
    Keywords Radiotherapy/Data processing ; Cancer/Radiotherapy/Data processing ; Medical physics/Data processing
    Language English
    Dates of publication 2023-2023
    Size xii, 171 pages ;, 24 cm
    Publisher CRC Press
    Publishing place Boca Raton, FL
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 9780367538101 ; 0367538105
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online ; Conference proceedings ; E-Book: Applications of Medical Artificial Intelligence

    Shabestari, Behrouz / Xing, Lei / Wu, Shandong

    First International Workshop, AMAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

    (Lecture Notes in Computer Science, ; 13540)

    2022  

    Abstract: This book constitutes the refereed proceedings of the first International Workshop on Applications of Medical Artificial Intelligence, AMAI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The book includes 17 papers which ... ...

    Author's details edited by Shandong Wu, Behrouz Shabestari, Lei Xing
    Series title Lecture Notes in Computer Science, ; 13540
    Lecture notes in computer science
    Collection Lecture notes in computer science
    Abstract This book constitutes the refereed proceedings of the first International Workshop on Applications of Medical Artificial Intelligence, AMAI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The book includes 17 papers which were carefully reviewed and selected from 26 full-length submissions. Practical applications of medical AI bring in new challenges and opportunities. The AMAI workshop aims to engage medical AI practitioners and bring more application flavor in clinical, evaluation, human-AI collaboration, new technical strategy, trustfulness, etc., to augment the research and development on the application aspects of medical AI, on top of pure technical research.
    Keywords Computer vision ; Application software ; Artificial intelligence ; Education/Data processing ; Social sciences/Data processing ; Computer Vision ; Computer and Information Systems Applications ; Artificial Intelligence ; Computers and Education ; Computer Application in Social and Behavioral Sciences
    Subject code 006.3
    Language English
    Size 1 online resource (171 pages)
    Edition 1st ed. 2022.
    Publisher Springer Nature Switzerland ; Imprint: Springer
    Publishing place Cham
    Document type Book ; Online ; Conference proceedings ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 3-031-17721-5 ; 9783031177200 ; 978-3-031-17721-7 ; 3031177207
    DOI 10.1007/978-3-031-17721-7
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Book ; Online ; E-Book: Big data in radiation oncology

    Deng, Jun / Xing, Lei

    (Imaging in medical diagnosis and therapy ; 30)

    2019  

    Author's details edited by Jun Deng, Lei Xing
    Series title Imaging in medical diagnosis and therapy ; 30
    Collection
    Keywords Radiation Oncology ; Data Mining / methods
    Language English
    Size 1 Online-Ressource (xx, 289 Seiten), Illustrationen, Diagramme
    Publisher CRC Press, Taylor & Francis Group
    Publishing place Boca Raton
    Publishing country United States
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020043626
    ISBN 978-1-351-80112-6 ; 9781138633438 ; 1-351-80112-0 ; 1138633437
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Book ; Online ; E-Book: Artificial intelligence in medicine

    Min, James K. / Xing, Lei / Giger, Maryellen Lissak

    technical basis and clinical applications

    2021  

    Author's details edited by Lei Xing, Maryellen L. Giger, James K. Min
    Keywords Artificial intelligence ; Artificial intelligence/Medical applications
    Subject code 610.28563
    Language English
    Size 1 online resource (570 pages) :, illustrations
    Publisher Academic Press ; Elsevier
    Publishing place London
    Document type Book ; Online ; E-Book
    Note Includes index.
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 0-12-821258-6 ; 0-12-821259-4 ; 978-0-12-821258-5 ; 978-0-12-821259-2
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  5. Book ; Online: Machine Learning With Radiation Oncology Big Data

    Xing, Lei / Naqa, Issam El / Deng, Jun

    2019  

    Keywords Neoplasms. Tumors. Oncology. Including cancer and carcinogens ; Medicine (General)
    Size 1 electronic resource (146 p.)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT020101992
    ISBN 9782889457304 ; 2889457303
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  6. Book ; Online ; E-Book: Radiomics and radiogenomics

    Li, Ruijiang / Xing, Lei / Napel, Sandy / Rubin, Daniel

    technical basis and clinical applications

    (Imaging in medical diagnosis and therapy)

    2019  

    Author's details edited by Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin
    Series title Imaging in medical diagnosis and therapy
    Keywords Cancer/Imaging ; Diagnostic imaging
    Subject code 616.9940754
    Language English
    Size 1 Online-Ressource (xxii, 419 Seiten), Illustrationen
    Publisher CRC Press
    Publishing place Boca Raton, FL
    Publishing country United States
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020188395
    ISBN 978-1-3512-0825-3 ; 978-1-3512-0826-0 ; 978-1-3512-0824-6 ; 978-1-3512-0827-7 ; 9780815375852 ; 1-3512-0825-X ; 1-3512-0826-8 ; 1-3512-0824-1 ; 1-3512-0827-6 ; 0815375859
    DOI 10.1201/9781351208277
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    Full text online

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  7. Book: Image guided and adaptive radiation therapy

    Timmerman, Robert D. / Xing, Lei

    2010  

    Title variant Radiation therapy ; Image-guided and adaptive radiation therapy
    Author's details Robert Timmerman ; Lei Xing
    Keywords Radiotherapy, Computer-Assisted / methods ; Neoplasms / radiotherapy ; Image-guided radiation therapy
    Subject code 616.9940642
    Language English
    Size XVI, 367 S. : zahlr. Ill., graph. Darst.
    Publisher Wolters Kluwer, Lippincott Williams & Wilkins
    Publishing place Philadelphia u.a.
    Publishing country United States
    Document type Book
    Note Includes bibliographical references and index
    Accompanying material Zugang zur Internetausgabe über Code
    HBZ-ID HT016155250
    ISBN 978-0-7817-8282-1 ; 0-7817-8282-1
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2009 A 6245 order for loan Magazin
    Zugang zur Internetausgabe über Code aus lizenzrechtlichen Gründen nicht verfügbar

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  8. Book ; Online: Image-guided and adaptive radiation therapy

    Timmerman, Robert D. / Xing, Lei

    2010  

    Author's details [edited by] Robert Timmerman, Lei Xing
    Keywords Radiotherapy, computer-assisted - methods ; Neoplasms - radiotherapy
    Language English
    Size 1 Online-Ressource
    Publisher Wolters Kluwer Lippincott Williams & Wilkins Health
    Publishing place Philadelphia
    Document type Book ; Online
    Note Includes bibliographical references and index
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 978-0-7817-8282-1 ; 0-7817-8282-1
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    Full text online

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  9. Article ; Online: Deciphering the Feature Representation of Deep Neural Networks for High-Performance AI.

    Islam, Md Tauhidul / Xing, Lei

    IEEE transactions on pattern analysis and machine intelligence

    2024  Volume PP

    Abstract: AI driven by deep learning is transforming many aspects of science and technology. The enormous success of deep learning stems from its unique capability of extracting essential features from Big Data for decision-making. However, the feature extraction ... ...

    Abstract AI driven by deep learning is transforming many aspects of science and technology. The enormous success of deep learning stems from its unique capability of extracting essential features from Big Data for decision-making. However, the feature extraction and hidden representations in deep neural networks (DNNs) remain inexplicable, primarily because of lack of technical tools to comprehend and interrogate the feature space data. The main hurdle here is that the feature data are often noisy in nature, complex in structure, and huge in size and dimensionality, making it intractable for existing techniques to analyze the data reliably. In this work, we develop a computational framework named contrastive feature analysis (CFA) to facilitate the exploration of the DNN feature space and improve the performance of AI. By utilizing the interaction relations among the features and incorporating a novel data-driven kernel formation strategy into the feature analysis pipeline, CFA mitigates the limitations of traditional approaches and provides an urgently needed solution for the analysis of feature space data. The technique allows feature data exploration in unsupervised, semi-supervised and supervised formats to address different needs of downstream applications. The potential of CFA and its applications for pruning of neural network architectures are demonstrated using several state-of-the-art networks and well-annotated datasets across different disciplines.
    Language English
    Publishing date 2024-02-19
    Publishing country United States
    Document type Journal Article
    ISSN 1939-3539
    ISSN (online) 1939-3539
    DOI 10.1109/TPAMI.2024.3363642
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data.

    Islam, Md Tauhidul / Xing, Lei

    Patterns (New York, N.Y.)

    2023  Volume 4, Issue 10, Page(s) 100840

    Abstract: Single-cell trajectory mapping and spatial reconstruction are two important developments in life science and provide a unique means to decode heterogeneous tissue formation, cellular dynamics, and tissue developmental processes. The success of these ... ...

    Abstract Single-cell trajectory mapping and spatial reconstruction are two important developments in life science and provide a unique means to decode heterogeneous tissue formation, cellular dynamics, and tissue developmental processes. The success of these techniques depends critically on the performance of analytical tools used for high-dimensional (HD) gene expression data processing. Existing methods discern the patterns of the data without explicitly considering the underlying biological characteristics of the system, often leading to suboptimal solutions. Here, we present a cell-cell similarity-driven framework of genomic data analysis for high-fidelity spatial and temporal cellular mappings. The approach exploits the similarity features of the cells to discover discriminative patterns of the data. We show that for a wide variety of datasets, the proposed approach drastically improves the accuracies of spatial and temporal mapping analyses compared with state-of-the-art techniques.
    Language English
    Publishing date 2023-09-07
    Publishing country United States
    Document type Journal Article
    ISSN 2666-3899
    ISSN (online) 2666-3899
    DOI 10.1016/j.patter.2023.100840
    Database MEDical Literature Analysis and Retrieval System OnLINE

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