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  1. Buch ; Dissertation / Habilitation: Das Karpaltunnelsyndrom - Rezidive

    Klein, Inga

    Häufigkeit und deren Auftreten im zeitlichen Verlauf nach operativer Versorgung; eine retrospektive Analyse über einen Zeitraum von 13 Jahren

    2010  

    Verfasserangabe vorgelegt von Inga Klein
    Sprache Deutsch
    Umfang IX, 139 S. : Ill., graph. Darst.
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Köln, Univ., Diss., 2010
    HBZ-ID HT016476032
    Datenquelle Katalog ZB MED Medizin, Gesundheit

    Kategorien

  2. Artikel: Effects of Radioiodine on the Nasolacrimal System.

    Klein, Irwin

    Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists

    2022  Band 28, Heft 12, Seite(n) 1272–1273

    Mesh-Begriff(e) Humans ; Iodine Radioisotopes/adverse effects
    Chemische Substanzen Iodine Radioisotopes
    Sprache Englisch
    Erscheinungsdatum 2022-09-26
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 1473503-9
    ISSN 1530-891X
    ISSN 1530-891X
    DOI 10.1016/j.eprac.2022.09.004
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Private Payers and Cancer Care: Revisiting the Land of Opportunity.

    Kolodziej, Michael A / Klein, Ira

    JCO oncology practice

    2024  Band 20, Heft 3, Seite(n) 318–322

    Abstract: Ten years ago we charted a course for oncology payment reform. We summarize what went wrong and propose ways to fix it. ...

    Abstract Ten years ago we charted a course for oncology payment reform. We summarize what went wrong and propose ways to fix it.
    Mesh-Begriff(e) Humans ; Neoplasms/epidemiology ; Neoplasms/therapy ; Medical Oncology
    Sprache Englisch
    Erscheinungsdatum 2024-01-05
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 3028198-2
    ISSN 2688-1535 ; 2688-1527
    ISSN (online) 2688-1535
    ISSN 2688-1527
    DOI 10.1200/OP.23.00632
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Buch ; Online: Data-Driven Meets Navigation

    Klein, Itzik

    Concepts, Models, and Experimental Validation

    2022  

    Abstract: The purpose of navigation is to determine the position, velocity, and orientation of manned and autonomous platforms, humans, and animals. Obtaining accurate navigation commonly requires fusion between several sensors, such as inertial sensors and global ...

    Abstract The purpose of navigation is to determine the position, velocity, and orientation of manned and autonomous platforms, humans, and animals. Obtaining accurate navigation commonly requires fusion between several sensors, such as inertial sensors and global navigation satellite systems, in a model-based, nonlinear estimation framework. Recently, data-driven approaches applied in various fields show state-of-the-art performance, compared to model-based methods. In this paper we review multidisciplinary, data-driven based navigation algorithms developed and experimentally proven at the Autonomous Navigation and Sensor Fusion Lab (ANSFL) including algorithms suitable for human and animal applications, varied autonomous platforms, and multi-purpose navigation and fusion approaches

    Comment: 22 pages, 13 figures
    Schlagwörter Computer Science - Robotics ; Computer Science - Artificial Intelligence
    Erscheinungsdatum 2022-10-06
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Buch ; Online: A-KIT

    Cohen, Nadav / Klein, Itzik

    Adaptive Kalman-Informed Transformer

    2024  

    Abstract: The extended Kalman filter (EKF) is a widely adopted method for sensor fusion in navigation applications. A crucial aspect of the EKF is the online determination of the process noise covariance matrix reflecting the model uncertainty. While common EKF ... ...

    Abstract The extended Kalman filter (EKF) is a widely adopted method for sensor fusion in navigation applications. A crucial aspect of the EKF is the online determination of the process noise covariance matrix reflecting the model uncertainty. While common EKF implementation assumes a constant process noise, in real-world scenarios, the process noise varies, leading to inaccuracies in the estimated state and potentially causing the filter to diverge. To cope with such situations, model-based adaptive EKF methods were proposed and demonstrated performance improvements, highlighting the need for a robust adaptive approach. In this paper, we derive and introduce A-KIT, an adaptive Kalman-informed transformer to learn the varying process noise covariance online. The A-KIT framework is applicable to any type of sensor fusion. Here, we present our approach to nonlinear sensor fusion based on an inertial navigation system and Doppler velocity log. By employing real recorded data from an autonomous underwater vehicle, we show that A-KIT outperforms the conventional EKF by more than 49.5% and model-based adaptive EKF by an average of 35.4% in terms of position accuracy.
    Schlagwörter Computer Science - Robotics ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Systems and Control
    Thema/Rubrik (Code) 000
    Erscheinungsdatum 2024-01-18
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Data-Driven Strategies for Coping with Incomplete DVL Measurements

    Cohen, Nadav / Klein, Itzik

    2024  

    Abstract: Autonomous underwater vehicles are specialized platforms engineered for deep underwater operations. Critical to their functionality is autonomous navigation, typically relying on an inertial navigation system and a Doppler velocity log. In real-world ... ...

    Abstract Autonomous underwater vehicles are specialized platforms engineered for deep underwater operations. Critical to their functionality is autonomous navigation, typically relying on an inertial navigation system and a Doppler velocity log. In real-world scenarios, incomplete Doppler velocity log measurements occur, resulting in positioning errors and mission aborts. To cope with such situations, a model and learning approaches were derived. This paper presents a comparative analysis of two cutting-edge deep learning methodologies, namely LiBeamsNet and MissBeamNet, alongside a model-based average estimator. These approaches are evaluated for their efficacy in regressing missing Doppler velocity log beams when two beams are unavailable. In our study, we used data recorded by a DVL mounted on an autonomous underwater vehicle operated in the Mediterranean Sea. We found that both deep learning architectures outperformed model-based approaches by over 16% in velocity prediction accuracy.
    Schlagwörter Computer Science - Robotics ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Signal Processing ; Electrical Engineering and Systems Science - Systems and Control
    Thema/Rubrik (Code) 629
    Erscheinungsdatum 2024-01-28
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Buch ; Dissertation / Habilitation: Retrospektive Analyse der Therapie von Extrauteringraviditäten an der Universitäts-Frauenklinik Homburg

    Klein, Isabel

    2002  

    Verfasserangabe vorgelegt von Isabel Klein
    Sprache Deutsch
    Umfang 54 Bl. : Ill., graph. Darst.
    Ausgabenhinweis [Mikrofiche-Ausg.]
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Saarbrücken, Univ., Diss., 2003
    HBZ-ID HT013935602
    Datenquelle Katalog ZB MED Medizin, Gesundheit

    Kategorien

  8. Artikel ; Online: Smartphone Location Recognition: A Deep Learning-Based Approach.

    Klein, Itzik

    Sensors (Basel, Switzerland)

    2019  Band 20, Heft 1

    Abstract: One of the approaches for indoor positioning using smartphones is pedestrian dead reckoning. There, the user step length is estimated using empirical or biomechanical formulas. Such calculation was shown to be very sensitive to the smartphone location on ...

    Abstract One of the approaches for indoor positioning using smartphones is pedestrian dead reckoning. There, the user step length is estimated using empirical or biomechanical formulas. Such calculation was shown to be very sensitive to the smartphone location on the user. In addition, knowledge of the smartphone location can also help for direct step-length estimation and heading determination. In a wider point of view, smartphone location recognition is part of human activity recognition employed in many fields and applications, such as health monitoring. In this paper, we propose to use deep learning approaches to classify the smartphone location on the user, while walking, and require robustness in terms of the ability to cope with recordings that differ (in sampling rate, user dynamics, sensor type, and more) from those available in the train dataset. The contributions of the paper are: (1) Definition of the smartphone location recognition framework using accelerometers, gyroscopes, and deep learning; (2) examine the proposed approach on 107 people and 31 h of recorded data obtained from eight different datasets; and (3) enhanced algorithms for using only accelerometers for the classification process. The experimental results show that the smartphone location can be classified with high accuracy using only the smartphone's accelerometers.
    Sprache Englisch
    Erscheinungsdatum 2019-12-30
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s20010214
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Buch ; Dissertation / Habilitation: Zelluläre Immunreaktionen nach orthotoper Rattenlebertransplantation unter selektiver immunsuppressiver Therapie und Toleranzinduktion

    Klein, Ingo

    2000  

    Verfasserangabe vorgelegt von Ingo Klein
    Sprache Deutsch
    Umfang 93 S., Ill., graph. Darst., 21 cm
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Würzburg, Univ., Diss., 2001
    HBZ-ID HT013203499
    Datenquelle Katalog ZB MED Medizin, Gesundheit

    Kategorien

  10. Artikel: Hochmoderne Labore auf dem Onkologischen Campus der Dresdner Hochschulmedizin

    Mallek-Klein, I. / Meinhardt, A.

    Krebs im Focus

    2021  Band 13, Heft Juni, Seite(n) 261

    Sprache Deutsch
    Dokumenttyp Artikel
    ZDB-ID 2761631-9
    Datenquelle Current Contents Medizin

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