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  1. Article: 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  Volume 28, Issue 12, Page(s) 1272–1273

    MeSH term(s) Humans ; Iodine Radioisotopes/adverse effects
    Chemical Substances Iodine Radioisotopes
    Language English
    Publishing date 2022-09-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1473503-9
    ISSN 1530-891X
    ISSN 1530-891X
    DOI 10.1016/j.eprac.2022.09.004
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5034: 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)
    Zs.MO 508: Show issues

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  2. Book ; Thesis: 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  

    Author's details vorgelegt von Inga Klein
    Language German
    Size IX, 139 S. : Ill., graph. Darst.
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Köln, Univ., Diss., 2010
    HBZ-ID HT016476032
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2010 D 723 order for loan Magazin

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

    Kolodziej, Michael A / Klein, Ira

    JCO oncology practice

    2024  Volume 20, Issue 3, Page(s) 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 term(s) Humans ; Neoplasms/epidemiology ; Neoplasms/therapy ; Medical Oncology
    Language English
    Publishing date 2024-01-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3028198-2
    ISSN 2688-1535 ; 2688-1527
    ISSN (online) 2688-1535
    ISSN 2688-1527
    DOI 10.1200/OP.23.00632
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; 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
    Keywords Computer Science - Robotics ; Computer Science - Artificial Intelligence
    Publishing date 2022-10-06
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Smartphone Location Recognition: A Deep Learning-Based Approach.

    Klein, Itzik

    Sensors (Basel, Switzerland)

    2019  Volume 20, Issue 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.
    Language English
    Publishing date 2019-12-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s20010214
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  6. Book ; 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.
    Keywords Computer Science - Robotics ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Systems and Control
    Subject code 000
    Publishing date 2024-01-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; 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.
    Keywords Computer Science - Robotics ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Signal Processing ; Electrical Engineering and Systems Science - Systems and Control
    Subject code 629
    Publishing date 2024-01-28
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Thesis: Retrospektive Analyse der Therapie von Extrauteringraviditäten an der Universitäts-Frauenklinik Homburg

    Klein, Isabel

    2002  

    Author's details vorgelegt von Isabel Klein
    Language German
    Size 54 Bl. : Ill., graph. Darst.
    Edition [Mikrofiche-Ausg.]
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Saarbrücken, Univ., Diss., 2003
    HBZ-ID HT013935602
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2003 MB 104 order for loan Magazin

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  9. Article ; Online: Thyroid Abnormalities in Heart Failure.

    Danzi, Sara / Klein, Irwin

    Cardiology clinics

    2022  Volume 40, Issue 2, Page(s) 139–147

    Abstract: The effects of hyperthyroidism and hypothyroidism on the heart and cardiovascular system are well documented. It has also been shown that various forms of heart disease including but not limited to congenital, hypertensive, ischemic, cardiac surgery, and ...

    Abstract The effects of hyperthyroidism and hypothyroidism on the heart and cardiovascular system are well documented. It has also been shown that various forms of heart disease including but not limited to congenital, hypertensive, ischemic, cardiac surgery, and heart transplantation cause an alteration in thyroid function tests including a decrease in serum liothyronine (T
    MeSH term(s) Heart Failure/epidemiology ; Heart Failure/etiology ; Heart Failure/therapy ; Humans ; Hypothyroidism/complications ; Hypothyroidism/drug therapy ; Thyroid Diseases/drug therapy ; Triiodothyronine/therapeutic use
    Chemical Substances Triiodothyronine (06LU7C9H1V)
    Language English
    Publishing date 2022-03-31
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 1196385-2
    ISSN 1558-2264 ; 0733-8651
    ISSN (online) 1558-2264
    ISSN 0733-8651
    DOI 10.1016/j.ccl.2021.12.002
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  10. Article ; Online: QuadNet: A Hybrid Framework for Quadrotor Dead Reckoning.

    Shurin, Artur / Klein, Itzik

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 4

    Abstract: Quadrotor usage is continuously increasing for both civilian and military applications such as surveillance, mapping, and deliveries. Commonly, quadrotors use an inertial navigation system combined with a global navigation satellite systems receiver for ... ...

    Abstract Quadrotor usage is continuously increasing for both civilian and military applications such as surveillance, mapping, and deliveries. Commonly, quadrotors use an inertial navigation system combined with a global navigation satellite systems receiver for outdoor applications and a camera for indoor/outdoor applications. For various reasons, such as lighting conditions or satellite signal blocking, the quadrotor's navigation solution depends only on the inertial navigation system solution. As a consequence, the navigation solution drifts in time due to errors and noises in the inertial sensor measurements. To handle such situations and bind the solution drift, the quadrotor dead reckoning (QDR) approach utilizes pedestrian dead reckoning principles. To that end, instead of flying the quadrotor in a straight line trajectory, it is flown in a periodic motion, in the vertical plane, to enable peak-to-peak (two local maximum points within the cycle) distance estimation. Although QDR manages to improve the pure inertial navigation solution, it has several shortcomings as it requires calibration before usage, provides only peak-to-peak distance, and does not provide the altitude of the quadrotor. To circumvent these issues, we propose QuadNet, a hybrid framework for quadrotor dead reckoning to estimate the quadrotor's three-dimensional position vector at any user-defined time rate. As a hybrid approach, QuadNet uses both neural networks and model-based equations during its operation. QuadNet requires only the inertial sensor readings to provide the position vector. Experimental results with DJI's Matrice 300 quadrotor are provided to show the benefits of using the proposed approach.
    MeSH term(s) Algorithms ; Humans ; Lighting ; Motion ; Neural Networks, Computer ; Pedestrians
    Language English
    Publishing date 2022-02-13
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22041426
    Database MEDical Literature Analysis and Retrieval System OnLINE

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