LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 7 of total 7

Search options

  1. Book ; Online: Klinische Entscheidungsfindung mit Künstlicher Intelligenz

    Samhammer, David / Beck, Susanne / Budde, Klemens / Burchardt, Aljoscha / Faber, Michelle / Gerndt, Simon / Möller, Sebastian / Osmanodja, Bilgin / Roller, Roland / Dabrock, Peter

    Ein interdisziplinärer Governance-Ansatz

    (essentials)

    2023  

    Series title essentials
    Keywords Public health & preventive medicine ; Health economics ; Nursing ; Ethics & moral philosophy ; Renal medicine & nephrology ; Künstliche Intelligenz ; Maschinelles Lernen ; Medizin ; Klinik ; Entscheidungsfindung ; Meaningful Human Control ; Bedeutsame menschliche Kontrolle ; Governance ; Medizinische Unterstützungssysteme
    Language German
    Size 1 electronic resource (66 pages)
    Publisher Springer Nature
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    Note German
    HBZ-ID HT030378013
    ISBN 9783662670071 ; 3662670070
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Book ; Online: Klinische Entscheidungsfindung mit Künstlicher Intelligenz

    Samhammer, David / Beck, Susanne / Budde, Klemens / Burchardt, Aljoscha / Faber, Michelle / Gerndt, Simon / Möller, Sebastian / Osmanodja, Bilgin / Roller, Roland / Dabrock, Peter

    Ein interdisziplinärer Governance-Ansatz

    (essentials)

    2023  

    Author's details von David Samhammer, Susanne Beck, Klemens Budde, Aljoscha Burchardt, Michelle Faber, Simon Gerndt, Sebastian Möller, Bilgin Osmanodja, Roland Roller, Peter Dabrock
    Series title essentials
    Keywords Public health ; Medical care ; Medical Ethics ; Nursing ethics ; Technology—Moral and ethical aspects ; Nephrology
    Language German
    Size 1 Online-Ressource (XI, 66 S. 1 Abb)
    Edition 1st ed. 2023
    Publisher Springer Berlin Heidelberg ; Imprint: Springer
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    HBZ-ID HT030028617
    ISBN 978-3-662-67008-8 ; 9783662670071 ; 3-662-67008-9 ; 3662670070
    DOI 10.1007/978-3-662-67008-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article ; Online: For the sake of multifacetedness. Why artificial intelligence patient preference prediction systems shouldn't be for next of kin.

    Tretter, Max / Samhammer, David

    Journal of medical ethics

    2023  Volume 49, Issue 3, Page(s) 175–176

    MeSH term(s) Humans ; Artificial Intelligence ; Patient Preference
    Language English
    Publishing date 2023-01-10
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 194927-5
    ISSN 1473-4257 ; 0306-6800
    ISSN (online) 1473-4257
    ISSN 0306-6800
    DOI 10.1136/jme-2022-108775
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 1163: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  4. Article: Investigating the Impact of AI on Shared Decision-Making in Post-Kidney Transplant Care (PRIMA-AI): Protocol for a Randomized Controlled Trial.

    Osmanodja, Bilgin / Sassi, Zeineb / Eickmann, Sascha / Hansen, Carla Maria / Roller, Roland / Burchardt, Aljoscha / Samhammer, David / Dabrock, Peter / Möller, Sebastian / Budde, Klemens / Herrmann, Anne

    JMIR research protocols

    2024  Volume 13, Page(s) e54857

    Abstract: Background: Patients after kidney transplantation eventually face the risk of graft loss with the concomitant need for dialysis or retransplantation. Choosing the right kidney replacement therapy after graft loss is an important preference-sensitive ... ...

    Abstract Background: Patients after kidney transplantation eventually face the risk of graft loss with the concomitant need for dialysis or retransplantation. Choosing the right kidney replacement therapy after graft loss is an important preference-sensitive decision for kidney transplant recipients. However, the rate of conversations about treatment options after kidney graft loss has been shown to be as low as 13% in previous studies. It is unknown whether the implementation of artificial intelligence (AI)-based risk prediction models can increase the number of conversations about treatment options after graft loss and how this might influence the associated shared decision-making (SDM).
    Objective: This study aims to explore the impact of AI-based risk prediction for the risk of graft loss on the frequency of conversations about the treatment options after graft loss, as well as the associated SDM process.
    Methods: This is a 2-year, prospective, randomized, 2-armed, parallel-group, single-center trial in a German kidney transplant center. All patients will receive the same routine post-kidney transplant care that usually includes follow-up visits every 3 months at the kidney transplant center. For patients in the intervention arm, physicians will be assisted by a validated and previously published AI-based risk prediction system that estimates the risk for graft loss in the next year, starting from 3 months after randomization until 24 months after randomization. The study population will consist of 122 kidney transplant recipients >12 months after transplantation, who are at least 18 years of age, are able to communicate in German, and have an estimated glomerular filtration rate <30 mL/min/1.73 m
    Results: The enrollment for the study is ongoing. The first results are expected to be submitted for publication in 2025.
    Conclusions: This is the first study to examine the influence of AI-based risk prediction on physician-patient interaction in the context of kidney transplantation. We use a mixed methods approach by combining a randomized design with a simple quantitative end point (frequency of conversations), different quantitative measurements for SDM, and several qualitative research methods (eg, records of physician-patient conversations and semistructured interviews) to examine the implementation of AI-based risk prediction in the clinic.
    Trial registration: ClinicalTrials.gov NCT06056518; https://clinicaltrials.gov/study/NCT06056518.
    International registered report identifier (irrid): PRR1-10.2196/54857.
    Language English
    Publishing date 2024-04-01
    Publishing country Canada
    Document type Journal Article
    ZDB-ID 2719222-2
    ISSN 1929-0748
    ISSN 1929-0748
    DOI 10.2196/54857
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  5. Article ; Online: When performance is not enough-A multidisciplinary view on clinical decision support.

    Roller, Roland / Burchardt, Aljoscha / Samhammer, David / Ronicke, Simon / Duettmann, Wiebke / Schmeier, Sven / Möller, Sebastian / Dabrock, Peter / Budde, Klemens / Mayrdorfer, Manuel / Osmanodja, Bilgin

    PloS one

    2023  Volume 18, Issue 4, Page(s) e0282619

    Abstract: Scientific publications about the application of machine learning models in healthcare often focus on improving performance metrics. However, beyond often short-lived improvements, many additional aspects need to be taken into consideration to make ... ...

    Abstract Scientific publications about the application of machine learning models in healthcare often focus on improving performance metrics. However, beyond often short-lived improvements, many additional aspects need to be taken into consideration to make sustainable progress. What does it take to implement a clinical decision support system, what makes it usable for the domain experts, and what brings it eventually into practical usage? So far, there has been little research to answer these questions. This work presents a multidisciplinary view of machine learning in medical decision support systems and covers information technology, medical, as well as ethical aspects. The target audience is computer scientists, who plan to do research in a clinical context. The paper starts from a relatively straightforward risk prediction system in the subspecialty nephrology that was evaluated on historic patient data both intrinsically and based on a reader study with medical doctors. Although the results were quite promising, the focus of this article is not on the model itself or potential performance improvements. Instead, we want to let other researchers participate in the lessons we have learned and the insights we have gained when implementing and evaluating our system in a clinical setting within a highly interdisciplinary pilot project in the cooperation of computer scientists, medical doctors, ethicists, and legal experts.
    MeSH term(s) Humans ; Decision Support Systems, Clinical ; Pilot Projects ; Delivery of Health Care ; Publications ; Physicians
    Language English
    Publishing date 2023-04-24
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0282619
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  6. Book ; Online: When Performance is not Enough -- A Multidisciplinary View on Clinical Decision Support

    Roller, Roland / Budde, Klemens / Burchardt, Aljoscha / Dabrock, Peter / Möller, Sebastian / Osmanodja, Bilgin / Ronicke, Simon / Samhammer, David / Schmeier, Sven

    2022  

    Abstract: Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective. However, beyond such often short-lived improvements, much more needs to ... ...

    Abstract Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective. However, beyond such often short-lived improvements, much more needs to be taken into consideration if we want to arrive at a sustainable progress in healthcare. What does it take to actually implement such a system, make it usable for the domain expert, and possibly bring it into practical usage? Targeted at Computer Scientists, this work presents a multidisciplinary view on machine learning in medical decision support systems and covers information technology, medical, as well as ethical aspects. Along with an implemented risk prediction system in nephrology, challenges and lessons learned in a pilot project are presented.

    Comment: Paper currently under review
    Keywords Computer Science - Machine Learning ; Computer Science - Computers and Society
    Subject code 006
    Publishing date 2022-04-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  7. Conference proceedings: PRIMA AI – prospectively investigating the impact of AI on shared decision making in post-kidney transplant care

    Eickmann, Sascha / Sassi, Zeineb / Dabrock, Peter / Samhammer, David / Budde, Klemens / Osmanodja, Bilgin / Möller, Sebastian / Roller, Roland / Burchardt, Aljoscha / Herrmann-Johns, Anne

    2023  , Page(s) 23dkvf251

    Event/congress 22. Deutscher Kongress für Versorgungsforschung (DKVF); Berlin; Deutsches Netzwerk Versorgungsforschung; 2023
    Keywords Medizin, Gesundheit
    Publishing date 2023-10-02
    Publisher German Medical Science GMS Publishing House; Düsseldorf
    Document type Conference proceedings
    DOI 10.3205/23dkvf251
    Database German Medical Science

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top