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  1. Article ; Online: TCRs and AI: the future is now.

    Sim, Malcolm J W

    Nature reviews. Immunology

    2023  Volume 24, Issue 1, Page(s) 3

    MeSH term(s) Humans ; Receptors, Antigen, T-Cell/genetics ; CD8-Positive T-Lymphocytes
    Chemical Substances Receptors, Antigen, T-Cell
    Language English
    Publishing date 2023-12-06
    Publishing country England
    Document type Journal Article
    ZDB-ID 2062776-2
    ISSN 1474-1741 ; 1474-1733
    ISSN (online) 1474-1741
    ISSN 1474-1733
    DOI 10.1038/s41577-023-00974-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5565: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MG 34: Show issues

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  2. Article ; Online: The COVID-19 pandemic: major risks to healthcare and other workers on the front line.

    Sim, Malcolm R

    Occupational and environmental medicine

    2020  Volume 77, Issue 5, Page(s) 281–282

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections/epidemiology ; Health Personnel ; Humans ; Occupational Exposure ; Pandemics ; Pneumonia, Viral/epidemiology ; Risk ; SARS-CoV-2
    Keywords covid19
    Language English
    Publishing date 2020-04-01
    Publishing country England
    Document type Editorial
    ZDB-ID 1180733-7
    ISSN 1470-7926 ; 1351-0711
    ISSN (online) 1470-7926
    ISSN 1351-0711
    DOI 10.1136/oemed-2020-106567
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Un I Zs.461: Show issues Location:
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  3. Article ; Online: Another changing of the guard at OEM, this time during the COVID-19 pandemic.

    Sim, Malcolm Ross

    Occupational and environmental medicine

    2020  Volume 77, Issue 7, Page(s) 429–430

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections ; Humans ; Pandemics ; Pneumonia, Viral ; SARS-CoV-2 ; Workload
    Keywords covid19
    Language English
    Publishing date 2020-06-02
    Publishing country England
    Document type Editorial ; Comment
    ZDB-ID 1180733-7
    ISSN 1470-7926 ; 1351-0711
    ISSN (online) 1470-7926
    ISSN 1351-0711
    DOI 10.1136/oemed-2020-106720
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Un I Zs.461: Show issues Location:
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  4. Article ; Online: Correspondence on 'Demographic, exposure and clinical characteristics in a multinational registry of engineered stone workers with silicosis' by Hua

    Hoy, Ryan F / Sim, Malcolm R

    Occupational and environmental medicine

    2022  

    Language English
    Publishing date 2022-06-23
    Publishing country England
    Document type Letter
    ZDB-ID 1180733-7
    ISSN 1470-7926 ; 1351-0711
    ISSN (online) 1470-7926
    ISSN 1351-0711
    DOI 10.1136/oemed-2022-108496
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Un I Zs.461: Show issues Location:
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  5. Article ; Online: The impact of inconsistent human annotations on AI driven clinical decision making.

    Sylolypavan, Aneeta / Sleeman, Derek / Wu, Honghan / Sim, Malcolm

    NPJ digital medicine

    2023  Volume 6, Issue 1, Page(s) 26

    Abstract: In supervised learning model development, domain experts are often used to provide the class labels (annotations). Annotation inconsistencies commonly occur when even highly experienced clinical experts annotate the same phenomenon (e.g., medical image, ... ...

    Abstract In supervised learning model development, domain experts are often used to provide the class labels (annotations). Annotation inconsistencies commonly occur when even highly experienced clinical experts annotate the same phenomenon (e.g., medical image, diagnostics, or prognostic status), due to inherent expert bias, judgments, and slips, among other factors. While their existence is relatively well-known, the implications of such inconsistencies are largely understudied in real-world settings, when supervised learning is applied on such 'noisy' labelled data. To shed light on these issues, we conducted extensive experiments and analyses on three real-world Intensive Care Unit (ICU) datasets. Specifically, individual models were built from a common dataset, annotated independently by 11 Glasgow Queen Elizabeth University Hospital ICU consultants, and model performance estimates were compared through internal validation (Fleiss' κ = 0.383 i.e., fair agreement). Further, broad external validation (on both static and time series datasets) of these 11 classifiers was carried out on a HiRID external dataset, where the models' classifications were found to have low pairwise agreements (average Cohen's κ = 0.255 i.e., minimal agreement). Moreover, they tend to disagree more on making discharge decisions (Fleiss' κ = 0.174) than predicting mortality (Fleiss' κ = 0.267). Given these inconsistencies, further analyses were conducted to evaluate the current best practices in obtaining gold-standard models and determining consensus. The results suggest that: (a) there may not always be a "super expert" in acute clinical settings (using internal and external validation model performances as a proxy); and (b) standard consensus seeking (such as majority vote) consistently leads to suboptimal models. Further analysis, however, suggests that assessing annotation learnability and using only 'learnable' annotated datasets for determining consensus achieves optimal models in most cases.
    Language English
    Publishing date 2023-02-21
    Publishing country England
    Document type Journal Article
    ISSN 2398-6352
    ISSN (online) 2398-6352
    DOI 10.1038/s41746-023-00773-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: Another changing of the guard at OEM, this time during the COVID-19 pandemic

    Sim, Malcolm Ross

    2020  

    Keywords Editorial ; covid19
    Language English
    Publishing date 2020-07-01 00:00:00.0
    Publisher BMJ Publishing Group Ltd
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: The COVID-19 pandemic

    Sim, Malcolm R

    major risks to healthcare and other workers on the front line

    2020  

    Keywords Editorial ; covid19
    Language English
    Publishing date 2020-05-01 00:00:00.0
    Publisher BMJ Publishing Group Ltd
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  10. Article ; Online: Another changing of the guard at OEM, this time during the COVID-19 pandemic

    Sim, Malcolm Ross

    Occupational and Environmental Medicine

    2020  Volume 77, Issue 7, Page(s) 429–430

    Keywords Public Health, Environmental and Occupational Health ; covid19
    Language English
    Publisher BMJ
    Publishing country uk
    Document type Article ; Online
    ZDB-ID 1180733-7
    ISSN 1470-7926 ; 1351-0711
    ISSN (online) 1470-7926
    ISSN 1351-0711
    DOI 10.1136/oemed-2020-106720
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Un I Zs.461: Show issues Location:
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