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  1. Book ; Online ; E-Book: Atlas Frühkarzinome des Gastrointestinaltrakts

    Berr, Frieder / Oyama, Tsuneo / Ponchon, Thierry / Yahagi, Naohisa

    endoskopische Diagnostik und Therapieentscheidungen

    2023  

    Abstract: Dieses Buch präsentiert die neuesten Standards und Erkenntnisse in der endoskopischen Diagnostik von Frühkarzinomen des gesamten Magen-Darm-Trakts. Der Atlas skizziert die Techniken und Strategien für die Detektion und das endoskopische Staging ( ... ...

    Author's details Frieder Berr, Tsuneo Oyama, Thierry Ponchon, Naohisa Yahagi (Hrsg.)
    Abstract Dieses Buch präsentiert die neuesten Standards und Erkenntnisse in der endoskopischen Diagnostik von Frühkarzinomen des gesamten Magen-Darm-Trakts. Der Atlas skizziert die Techniken und Strategien für die Detektion und das endoskopische Staging (Vorhersage der pT-Kategorie) von kleinen und winzigen Frühkarzinomen und zeigt, anhand von hochauflösenden endoskopischen und endo-sonographischen Abbildungen, Kriterien für die Invasion der Submukosa. Diese validierten Staging-Klassifikationen werden mit zahlreichen Bildern, Graphiken und strategischen Algorithmen erläutert. Für die kurative Resektion – dargestellt an histopathologischen Kriterien – werden auch die endoskopischen und laparoskopischen Resektionstechniken mit Risiken und Ergebnissen dargelegt – was eine evidenzbasierte Differentialindikation ermöglicht. Die Auflage umfasst auch die Diagnostik und Therapieindikation von Neoplasien im Dünndarm, Dysplasien / Frühkarzinomen bei Barrett Ösophagus und chronisch entzündlichen Darmerkrankungen sowie von submukösen Tumoren. Dieses Buch – mit führenden Experten verfasst - entspricht der in Japan und international anerkannten Diagnostik und ist für Endoskopiker eine wertvolle Quelle, um die Kompetenz in Diagnostik und Differentialindikation zu optimieren. Die Übersetzung wurde mit Hilfe von künstlicher Intelligenz durchgeführt. Eine anschließende menschliche Überarbeitung erfolgte vor allem in Bezug auf den Inhalt.
    Keywords Gastroenterology ; Internal medicine ; Surgery ; Oncology
    Language German
    Size 1 Online-Ressource (XIV, 335 Seiten), Illustrationen
    Publisher Springer
    Publishing place Cham
    Publishing country Switzerland
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT030598914
    ISBN 978-3-031-25623-3 ; 9783031256226 ; 3-031-25623-9 ; 3031256220
    DOI 10.1007/978-3-031-25623-3
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Is a traction device an almighty tool for overcoming the difficulties of endoscopic submucosal dissection?

    Yahagi, Naohisa

    Endoscopy

    2024  Volume 56, Issue 3, Page(s) 212–213

    MeSH term(s) Humans ; Endoscopic Mucosal Resection ; Traction ; Treatment Outcome ; Colorectal Neoplasms
    Language English
    Publishing date 2024-01-22
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-2234-8492
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online ; E-Book: Atlas of early neoplasias of the gastrointestinal tract

    Berr, Frieder / Oyama, Tsuneo / Ponchon, Thierry / Yahagi, Naohisa

    endoscopic diagnosis and therapeutic decisions

    2019  

    Author's details Frieder Berr, Tsuneo Oyama, Thierry Ponchon, Naochisa Yahagi editors
    Language English
    Size 1 Online-Ressource (xiv, 318 Seiten), Illustrationen, 23.5 cm x 15.5 cm
    Edition Second edition
    Publisher Springer
    Publishing place Cham
    Publishing country Switzerland
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020039135
    ISBN 978-3-030-01114-7 ; 9783030011130 ; 3-030-01114-3 ; 3030011135
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Article: Is a traction device an almighty tool for overcoming the difficulties of endoscopic submucosal dissection?

    Yahagi, Naohisa

    Endoscopy

    2024  Volume 56, Issue 03, Page(s) 212–213

    Language English
    Publishing date 2024-01-22
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-2234-8492
    Database Thieme publisher's database

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  5. Article ; Online: Development of colorectal endoscopic submucosal dissection.

    Yahagi, Naohisa

    Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society

    2022  Volume 34 Suppl 2, Page(s) 95–98

    MeSH term(s) Colonoscopy ; Colorectal Neoplasms/surgery ; Endoscopic Mucosal Resection ; Humans ; Treatment Outcome
    Language English
    Publishing date 2022-02-07
    Publishing country Australia
    Document type Editorial
    ZDB-ID 1171589-3
    ISSN 1443-1661 ; 0915-5635
    ISSN (online) 1443-1661
    ISSN 0915-5635
    DOI 10.1111/den.14229
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Is artificial intelligence ready to replace expert endoscopists?

    Yahagi, Naohisa

    Endoscopy

    2021  Volume 53, Issue 5, Page(s) 478–479

    MeSH term(s) Artificial Intelligence ; Deep Learning ; Endoscopy ; Humans ; Narrow Band Imaging ; Stomach Neoplasms
    Language English
    Publishing date 2021-04-22
    Publishing country Germany
    Document type Editorial ; Comment
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-1308-2121
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Reply to Drs. Liu and Yao.

    Kato, Motohiko / Yahagi, Naohisa

    Endoscopy

    2023  Volume 55, Issue 7, Page(s) 684

    Language English
    Publishing date 2023-06-28
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-2042-9806
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Is artificial intelligence ready to replace expert endoscopists?

    Yahagi, Naohisa

    Endoscopy

    2021  Volume 53, Issue 05, Page(s) 478–479

    Language English
    Publishing date 2021-04-22
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-1308-2121
    Database Thieme publisher's database

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  9. Article ; Online: Novel Approach for Detecting Respiratory Syncytial Virus in Pediatric Patients Using Machine Learning Models Based on Patient-Reported Symptoms: Model Development and Validation Study.

    Kawamoto, Shota / Morikawa, Yoshihiko / Yahagi, Naohisa

    JMIR formative research

    2024  Volume 8, Page(s) e52412

    Abstract: Background: Respiratory syncytial virus (RSV) affects children, causing serious infections, particularly in high-risk groups. Given the seasonality of RSV and the importance of rapid isolation of infected individuals, there is an urgent need for more ... ...

    Abstract Background: Respiratory syncytial virus (RSV) affects children, causing serious infections, particularly in high-risk groups. Given the seasonality of RSV and the importance of rapid isolation of infected individuals, there is an urgent need for more efficient diagnostic methods to expedite this process.
    Objective: This study aimed to investigate the performance of a machine learning model that leverages the temporal diversity of symptom onset for detecting RSV infections and elucidate its discriminatory ability.
    Methods: The study was conducted in pediatric and emergency outpatient settings in Japan. We developed a detection model that remotely confirms RSV infection based on patient-reported symptom information obtained using a structured electronic template incorporating the differential points of skilled pediatricians. An extreme gradient boosting-based machine learning model was developed using the data of 4174 patients aged ≤24 months who underwent RSV rapid antigen testing. These patients visited either the pediatric or emergency department of Yokohama City Municipal Hospital between January 1, 2009, and December 31, 2015. The primary outcome was the diagnostic accuracy of the machine learning model for RSV infection, as determined by rapid antigen testing, measured using the area under the receiver operating characteristic curve. The clinical efficacy was evaluated by calculating the discriminative performance based on the number of days elapsed since the onset of the first symptom and exclusion rates based on thresholds of reasonable sensitivity and specificity.
    Results: Our model demonstrated an area under the receiver operating characteristic curve of 0.811 (95% CI 0.784-0.833) with good calibration and 0.746 (95% CI 0.694-0.794) for patients within 3 days of onset. It accurately captured the temporal evolution of symptoms; based on adjusted thresholds equivalent to those of a rapid antigen test, our model predicted that 6.9% (95% CI 5.4%-8.5%) of patients in the entire cohort would be positive and 68.7% (95% CI 65.4%-71.9%) would be negative. Our model could eliminate the need for additional testing in approximately three-quarters of all patients.
    Conclusions: Our model may facilitate the immediate detection of RSV infection in outpatient settings and, potentially, in home environments. This approach could streamline the diagnostic process, reduce discomfort caused by invasive tests in children, and allow rapid implementation of appropriate treatments and isolation at home. The findings underscore the potential of machine learning in augmenting clinical decision-making in the early detection of RSV infection.
    Language English
    Publishing date 2024-04-12
    Publishing country Canada
    Document type Journal Article
    ISSN 2561-326X
    ISSN (online) 2561-326X
    DOI 10.2196/52412
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Layered closure by endoscopic hand suturing involving the muscle layer for large defect after gastric endoscopic submucosal dissection.

    Masunaga, Teppei / Yahagi, Naohisa / Kato, Motohiko

    Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society

    2024  Volume 36, Issue 3, Page(s) 384–385

    MeSH term(s) Humans ; Endoscopic Mucosal Resection ; Stomach ; Endoscopy ; Muscles ; Stomach Neoplasms/surgery
    Language English
    Publishing date 2024-01-11
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 1171589-3
    ISSN 1443-1661 ; 0915-5635
    ISSN (online) 1443-1661
    ISSN 0915-5635
    DOI 10.1111/den.14748
    Database MEDical Literature Analysis and Retrieval System OnLINE

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