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  1. Buch ; Dissertation / Habilitation: Malnutrition bei Patienten mit hepatozellulärem Karzinom

    Tippelt, Bernadett / Kahl, Stefan / Rau, Monika

    2022  

    Körperschaft Otto-von-Guericke-Universität Magdeburg
    Verfasserangabe von Bernadett Tippelt ; Gutachter: Prof. Dr. Stefan Kahl ; PD Dr. Monika Rau
    Schlagwörter Leberzellkrebs ; Mangelernährung
    Schlagwörter Malnutrition ; Leberzellkarzinom ; Hepatozelluläres Carcinom ; Hepatozelluläres Karzinom ; Primäres Leberzellkarzinom ; Malignes Hepatom
    Thema/Rubrik (Code) 610
    Sprache Deutsch
    Umfang 57 Blätter, Diagramme, Formular
    Verlag Otto-von-Guericke-Universität Magdeburg
    Erscheinungsort Magdeburg
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Dissertation, Universität Magdeburg, 2023
    HBZ-ID HT030638086
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  2. Buch: Arbeitsplatzbuch Endoskopie

    Gottschalk, Uwe / Maeting, Silvia / Kahl, Stefan

    zeitsparend Untersuchungen vorbereiten – fokussiert Wissen auffrischen

    2019  

    Verfasserangabe herausgegeben von Uwe Gottschalk, Silvia Maeting, Stefan Kahl ; unter Mitarbeit von David Albers [und vielen weiteren]
    Schlagwörter Bronchoskopie ; Duodenoskopie ; ERCP ; Endoskopie ; Gastroskopie ; Koloskopie ; Laparoskopie ; Polypektomie ; Sent ; endoskopische Eingriffe
    Schlagwörter Medizinische Endoskopie ; Endoskopische Untersuchung ; Diagnostische Endoskopie ; Spiegelung
    Thema/Rubrik (Code) 610
    Sprache Deutsch
    Umfang 440 Seiten, Illustrationen
    Verlag Georg Thieme Verlag
    Erscheinungsort Stuttgart
    Erscheinungsland Deutschland
    Dokumenttyp Buch
    HBZ-ID HT019872556
    ISBN 978-3-13-240593-6 ; 3-13-240593-0 ; 9783132405943 ; 9783132405950 ; 3132405949 ; 3132405957
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  3. Buch ; Dissertation / Habilitation: Prävalenz der bakteriellen Fehlbesiedlung des Dünndarms (SIBO) bei Patienten mit Leberzirrhose und ihr Einfluss auf das Vorliegen einer minimalen hepatischen Enzephalopathie

    Reisener, Nino / Kahl, Stefan / Mayerle, Julia

    2021  

    Titelvarianten Small Intestinal Bacterial Overgrowth
    Körperschaft Otto-von-Guericke-Universität Magdeburg
    Verfasserangabe von Nino Reisener ; Gutachter: Prof. Dr. Stefan Kahl ; Prof. Dr. Julia Mayerle
    Schlagwörter Leberzirrhose ; Encephalopathia hepatica ; Dünndarmfehlbesiedlung
    Schlagwörter DDFB ; Bakterielle Dünndarmfehlbesiedlung ; Small intestinal bacterial overgrowth ; Small intestinal bacterial overgrowth syndrome ; SIBO ; Small bowel (bacterial) overgrowth (syndrome) ; Hepatische Encephalopathie ; Portokavale Encephalopathie ; Portal-systemische Encephalopathie ; Portokavale Enzephalopathie ; Cirrhosis hepatis ; Hepatitis interstitialis chronica ; Hepatocirrhus ; Lebercirrhose ; Leberschrumpfung
    Sprache Deutsch
    Umfang 2 ungezählte Blätter, I, 61 Blätter, Illustrationen, Diagramme
    Verlag Otto-von-Guericke-Universität Magdeburg
    Erscheinungsort Magdeburg
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Dissertation, Universität Magdeburg, 2022
    HBZ-ID HT021843102
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  4. Buch ; Dissertation / Habilitation: Chronische Pankreatitis

    Kahl, Stefan

    Beitrag zur Optimierung des klinischen Managements

    2004  

    Verfasserangabe vorgelegt von Stefan Kahl
    Sprache Deutsch
    Umfang 138 Bl., graph. Darst., 30 cm
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Magdeburg, Univ., Habil.-Schr. (Nicht für den Austausch)
    HBZ-ID HT014862299
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  5. Artikel ; Online: Global birdsong embeddings enable superior transfer learning for bioacoustic classification.

    Ghani, Burooj / Denton, Tom / Kahl, Stefan / Klinck, Holger

    Scientific reports

    2023  Band 13, Heft 1, Seite(n) 22876

    Abstract: Automated bioacoustic analysis aids understanding and protection of both marine and terrestrial animals and their habitats across extensive spatiotemporal scales, and typically involves analyzing vast collections of acoustic data. With the advent of deep ...

    Abstract Automated bioacoustic analysis aids understanding and protection of both marine and terrestrial animals and their habitats across extensive spatiotemporal scales, and typically involves analyzing vast collections of acoustic data. With the advent of deep learning models, classification of important signals from these datasets has markedly improved. These models power critical data analyses for research and decision-making in biodiversity monitoring, animal behaviour studies, and natural resource management. However, deep learning models are often data-hungry and require a significant amount of labeled training data to perform well. While sufficient training data is available for certain taxonomic groups (e.g., common bird species), many classes (such as rare and endangered species, many non-bird taxa, and call-type) lack enough data to train a robust model from scratch. This study investigates the utility of feature embeddings extracted from audio classification models to identify bioacoustic classes other than the ones these models were originally trained on. We evaluate models on diverse datasets, including different bird calls and dialect types, bat calls, marine mammals calls, and amphibians calls. The embeddings extracted from the models trained on bird vocalization data consistently allowed higher quality classification than the embeddings trained on general audio datasets. The results of this study indicate that high-quality feature embeddings from large-scale acoustic bird classifiers can be harnessed for few-shot transfer learning, enabling the learning of new classes from a limited quantity of training data. Our findings reveal the potential for efficient analyses of novel bioacoustic tasks, even in scenarios where available training data is limited to a few samples.
    Mesh-Begriff(e) Animals ; Endangered Species ; Language ; Behavior, Animal ; Ecosystem ; Birds ; Machine Learning ; Mammals
    Sprache Englisch
    Erscheinungsdatum 2023-12-18
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-49989-z
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel: The Pierced Colon: When Biliary Stents Go the Wrong Way.

    Rybinski, Florian / Heinrich, Henriette / Zimmerli, Marius / Kahl, Stefan

    ACG case reports journal

    2023  Band 10, Heft 3, Seite(n) e01019

    Abstract: Bowel perforation of biliary stents is a rare complication of biliary stenting. We report the successful endoscopic treatment of a 78-year-old man with a straight biliary plastic stent perforating the ascending colon without underlying structural ... ...

    Abstract Bowel perforation of biliary stents is a rare complication of biliary stenting. We report the successful endoscopic treatment of a 78-year-old man with a straight biliary plastic stent perforating the ascending colon without underlying structural abnormality in the affected segment. Perforation was detected incidentally during computed tomography; the patient had been under continued antibiotic therapy for liver abscess. Stent extraction was performed by using an endoscopic snare; the site of perforation was closed with through-the-scope clips. The patient remained asymptomatic. In addition, we reviewed published cases of perforated biliary stents and outlined that most perforations are caused by straight plastic stents.
    Sprache Englisch
    Erscheinungsdatum 2023-04-03
    Erscheinungsland United States
    Dokumenttyp Case Reports
    ZDB-ID 2814825-3
    ISSN 2326-3253
    ISSN 2326-3253
    DOI 10.14309/crj.0000000000001019
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Pairing a user-friendly machine-learning animal sound detector with passive acoustic surveys for occupancy modeling of an endangered primate.

    Wood, Connor M / Barceinas Cruz, Alicia / Kahl, Stefan

    American journal of primatology

    2023  Band 85, Heft 8, Seite(n) e23507

    Abstract: Population declines and range contractions due to habitat loss are pervasive among nonhuman primates, with 60% of species threatened with extinction. However, the extensive vocal activity displayed by many primates makes them excellent candidates for ... ...

    Abstract Population declines and range contractions due to habitat loss are pervasive among nonhuman primates, with 60% of species threatened with extinction. However, the extensive vocal activity displayed by many primates makes them excellent candidates for passive acoustic surveys. Passive acoustic survey data is increasingly being used to support occupancy models, which have proven to be an efficient means of estimating both population trends and distributions. Passive acoustic surveys can be conducted relatively quickly and at broad scales, but efficient audio data processing has long proven elusive. The machine learning algorithm BirdNET was originally developed for birds but was recently expanded to include nonavian taxa. We demonstrate that BirdNET can accurately and efficiently identify an endangered primate, the Yucatán black howler monkey (Alouatta pigra), by sound in passive acoustic survey data (collected in southeastern Chiapas, Mexico), enabling us to use a single-season occupancy model to inform further survey efforts. Importantly, we also generated data on up to 286 co-occurring bird species, demonstrating the value of integrated animal sound classification tools for biodiversity surveys. BirdNET is freely available, requires no computer science expertise to use, and can readily be expanded to include more species (e.g., its species list recently tripled to >3000), suggesting that passive acoustic surveys, and thus occupancy modeling, for primate conservation could rapidly become much more accessible. Importantly, the long history of bioacoustics in primate research has yielded a wealth of information about their vocal behavior, which can facilitate appropriate survey design and data interpretation.
    Mesh-Begriff(e) Animals ; Conservation of Natural Resources ; Population Density ; Ecosystem ; Primates ; Acoustics
    Sprache Englisch
    Erscheinungsdatum 2023-05-21
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 1495834-X
    ISSN 1098-2345 ; 0275-2565
    ISSN (online) 1098-2345
    ISSN 0275-2565
    DOI 10.1002/ajp.23507
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Buch ; Dissertation / Habilitation: Früh- und Spätergebnisse nach endoskopischer und transduodenaler Sphincterotomie

    Kahl, Stefan

    eine retrospektive Untersuchung

    1995  

    Verfasserangabe vorgelegt von Stefan Kahl
    Sprache Deutsch
    Umfang 112 Bl. : graph. Darst.
    Erscheinungsland Deutschland
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation Magdeburg, Univ., Diss., 1996
    HBZ-ID HT007172996
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  9. Buch: Interventionelle Endoskopie

    Abou-Rebyeh, Hassan / Kahl, Stefan

    Lehrbuch und Atlas

    2007  

    Verfasserangabe hrsg. von Stefan Kahl ... Mit Beitr. von Hassan Abou-Rebyeh
    Schlagwörter Endoscopy, Gastrointestinal ; Gastrointestinal Diseases ; Verdauungskanal ; Krankheit ; Gastroenterologische Endoskopie
    Schlagwörter Gastrointestinale Endoskopie ; Magen-Darm-Kanal ; Erkrankung ; Krankheitszustand ; Krankheiten ; Morbus ; Nosos ; Pathos ; Canalis alimentorius ; Verdauungstrakt ; Verdauungsorgan ; Verdauungsapparat ; Apparatus digestorius ; Verdauungssystem
    Sprache Deutsch
    Umfang XVI, 416 S. : zahlr. Ill., graph. Darst.
    Ausgabenhinweis 1. Aufl.
    Verlag Elsevier, Urban & Fischer
    Erscheinungsort München u.a.
    Erscheinungsland Deutschland
    Dokumenttyp Buch
    HBZ-ID HT014858991
    ISBN 978-3-437-23620-4 ; 3-437-23620-2
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  10. Buch ; Online: Global birdsong embeddings enable superior transfer learning for bioacoustic classification

    Ghani, Burooj / Denton, Tom / Kahl, Stefan / Klinck, Holger

    2023  

    Abstract: Automated bioacoustic analysis aids understanding and protection of both marine and terrestrial animals and their habitats across extensive spatiotemporal scales, and typically involves analyzing vast collections of acoustic data. With the advent of deep ...

    Abstract Automated bioacoustic analysis aids understanding and protection of both marine and terrestrial animals and their habitats across extensive spatiotemporal scales, and typically involves analyzing vast collections of acoustic data. With the advent of deep learning models, classification of important signals from these datasets has markedly improved. These models power critical data analyses for research and decision-making in biodiversity monitoring, animal behaviour studies, and natural resource management. However, deep learning models are often data-hungry and require a significant amount of labeled training data to perform well. While sufficient training data is available for certain taxonomic groups (e.g., common bird species), many classes (such as rare and endangered species, many non-bird taxa, and call-type) lack enough data to train a robust model from scratch. This study investigates the utility of feature embeddings extracted from audio classification models to identify bioacoustic classes other than the ones these models were originally trained on. We evaluate models on diverse datasets, including different bird calls and dialect types, bat calls, marine mammals calls, and amphibians calls. The embeddings extracted from the models trained on bird vocalization data consistently allowed higher quality classification than the embeddings trained on general audio datasets. The results of this study indicate that high-quality feature embeddings from large-scale acoustic bird classifiers can be harnessed for few-shot transfer learning, enabling the learning of new classes from a limited quantity of training data. Our findings reveal the potential for efficient analyses of novel bioacoustic tasks, even in scenarios where available training data is limited to a few samples.
    Schlagwörter Electrical Engineering and Systems Science - Audio and Speech Processing ; Computer Science - Sound
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-07-12
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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