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  1. Article: Editorial: Advancing health equity through surgery: a review of recent contributions.

    Bandyopadhyay, Soham

    Frontiers in surgery

    2023  Volume 10, Page(s) 1292447

    Language English
    Publishing date 2023-09-21
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2773823-1
    ISSN 2296-875X
    ISSN 2296-875X
    DOI 10.3389/fsurg.2023.1292447
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Comment on: Global surgery education in Europe: a landscape analysis.

    Bandyopadhyay, Soham

    BJS open

    2022  Volume 6, Issue 2

    MeSH term(s) Educational Status ; Europe ; Humans
    Language English
    Publishing date 2022-02-26
    Publishing country England
    Document type Editorial ; Comment
    ISSN 2474-9842
    ISSN (online) 2474-9842
    DOI 10.1093/bjsopen/zrac037
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: In Reply to the Letter to the Editor Regarding "Traumatic Brain Injury-Related Pediatric Mortality and Morbidity in Low- and Middle-Income Countries: A Systematic Review".

    Bandyopadhyay, Soham

    World neurosurgery

    2022  Volume 157, Page(s) 256

    MeSH term(s) Brain Injuries, Traumatic/epidemiology ; Child ; Developing Countries ; Humans ; Income ; Morbidity
    Language English
    Publishing date 2022-01-06
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 2534351-8
    ISSN 1878-8769 ; 1878-8750
    ISSN (online) 1878-8769
    ISSN 1878-8750
    DOI 10.1016/j.wneu.2021.10.108
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  4. Article ; Online: Author's Reply: International Survey of Medical Students Exposure to Relevant Global Surgery (ISOMERS): A Cross-Sectional Study.

    Bandyopadhyay, Soham

    World journal of surgery

    2022  Volume 46, Issue 6, Page(s) 1512–1513

    MeSH term(s) Cross-Sectional Studies ; Humans ; Students, Medical ; Surveys and Questionnaires
    Language English
    Publishing date 2022-04-05
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 224043-9
    ISSN 1432-2323 ; 0364-2313
    ISSN (online) 1432-2323
    ISSN 0364-2313
    DOI 10.1007/s00268-022-06555-4
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  5. Article ; Online: Moving beyond diversity in curricula.

    Bandyopadhyay, Soham

    The clinical teacher

    2021  Volume 18, Issue 5, Page(s) 511–512

    MeSH term(s) Cultural Diversity ; Curriculum ; Humans
    Language English
    Publishing date 2021-08-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 2151518-9
    ISSN 1743-498X ; 1743-4971
    ISSN (online) 1743-498X
    ISSN 1743-4971
    DOI 10.1111/tct.13404
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  6. Article ; Online: Institutional racism and national lockdowns - Author's reply.

    Bandyopadhyay, Soham

    Lancet (London, England)

    2021  Volume 397, Issue 10283, Page(s) 1445–1446

    MeSH term(s) Humans ; Racism ; Systemic Racism
    Language English
    Publishing date 2021-04-17
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 3306-6
    ISSN 1474-547X ; 0023-7507 ; 0140-6736
    ISSN (online) 1474-547X
    ISSN 0023-7507 ; 0140-6736
    DOI 10.1016/S0140-6736(21)00240-3
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  7. Article ; Online: An institutionally racist lockdown policy.

    Bandyopadhyay, Soham

    Lancet (London, England)

    2020  Volume 396, Issue 10265, Page(s) 1802

    MeSH term(s) COVID-19/epidemiology ; COVID-19/prevention & control ; Humans ; Organizational Policy ; Pandemics ; Racism ; SARS-CoV-2 ; United Kingdom/epidemiology ; Universities
    Keywords covid19
    Language English
    Publishing date 2020-11-16
    Publishing country England
    Document type Letter
    ZDB-ID 3306-6
    ISSN 1474-547X ; 0023-7507 ; 0140-6736
    ISSN (online) 1474-547X
    ISSN 0023-7507 ; 0140-6736
    DOI 10.1016/S0140-6736(20)32464-8
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  8. Article ; Online: Letter to the Editor Regarding "Emerging Trends in the Neurosurgical Workforce of Low- and Middle-Income Countries: A Cross-Sectional Study".

    Bandyopadhyay, Soham

    World neurosurgery

    2020  Volume 143, Page(s) 605

    MeSH term(s) Cross-Sectional Studies ; Developing Countries ; Humans ; Income ; Neurosurgeons ; Workforce
    Language English
    Publishing date 2020-11-06
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2534351-8
    ISSN 1878-8769 ; 1878-8750
    ISSN (online) 1878-8769
    ISSN 1878-8750
    DOI 10.1016/j.wneu.2020.07.229
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  9. Article ; Online: Delivering medical leadership training through the Healthcare Leadership Academy: a four year analysis.

    Zarif, Azmaeen / Bandyopadhyay, Soham / Miller, George / Malawana, Johann

    BMC medical education

    2024  Volume 24, Issue 1, Page(s) 194

    Abstract: Background: Formal leadership training is typically targeted at senior health professionals. The Healthcare Leadership Academy (HLA) was formed in 2016 to provide a leadership programme for students and early-career health professionals. This study ... ...

    Abstract Background: Formal leadership training is typically targeted at senior health professionals. The Healthcare Leadership Academy (HLA) was formed in 2016 to provide a leadership programme for students and early-career health professionals. This study analyses the effectiveness of the HLA scholarship programme as an intervention for improving interest in and preparing scholars for future leadership roles.
    Methods: Survey data was used to assess the effectiveness of the HLA Scholarship program in cultivating leadership development. Questions required either multiple-choice, free text, ranking or Likert scale ('strongly agree', 'agree', 'neither agree nor disagree', 'disagree', 'strongly disagree) responses. Participants spanned six regions (London, Newcastle, Bristol, Belfast, Edinburgh, and Amsterdam) in four countries (England, Scotland, Northern Ireland, and the Netherlands). Descriptive statistical analyses were conducted, and insights were drawn from the open-ended survey questions using a leadership framework.
    Results: Seventy participants who underwent the course between 2016 and 2020 completed the questionnaire. Nearly all (99%) found that the training provided on the programme had equipped them to be more effective leaders, with 86% of respondents stating that they were more likely to take on leadership roles. Nearly all (97.1%) found the course to be either of good or very good quality. Nineteen insights were identified from free text responses that fitted under one of the four themes of the leadership framework: "optimising", "resolving uncertainty", "enhancing adaptability", and "promulgating a vision".
    Conclusions: Healthcare leadership is a non-negotiable component of healthcare delivery in the 21st Century. As healthcare professionals, it is our duty to be effective leaders confident and competent in navigating the increasingly complex systems within which we operate for the benefit of ourselves, colleagues, and patients. By accounting for known shortcomings and developing ameliorative measures, the HLA Scholarship programme addresses unmet needs in a structured manner to support effective long-term healthcare leadership development.
    MeSH term(s) Humans ; Leadership ; Delivery of Health Care ; Health Personnel/education ; England ; Scotland
    Language English
    Publishing date 2024-02-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2044473-4
    ISSN 1472-6920 ; 1472-6920
    ISSN (online) 1472-6920
    ISSN 1472-6920
    DOI 10.1186/s12909-024-05031-y
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  10. Article ; Online: Decoding Autism: Uncovering patterns in brain connectivity through sparsity analysis with rs-fMRI data.

    Bandyopadhyay, Soham / Peddi, Santhoshkumar / Sarma, Monalisa / Samanta, Debasis

    Journal of neuroscience methods

    2024  Volume 405, Page(s) 110100

    Abstract: Background: In the realm of neuro-disorders, precise diagnosis and treatment rely heavily on objective imaging-based biomarker identification. This study employs a sparsity approach on resting-state fMRI to discern relevant brain region connectivity for ...

    Abstract Background: In the realm of neuro-disorders, precise diagnosis and treatment rely heavily on objective imaging-based biomarker identification. This study employs a sparsity approach on resting-state fMRI to discern relevant brain region connectivity for predicting Autism.
    New method: The proposed methodology involves four key steps: (1) Utilizing three probabilistic brain atlases to extract functionally homogeneous brain regions from fMRI data. (2) Employing a hybrid approach of Graphical Lasso and Akaike Information Criteria to optimize sparse inverse covariance matrices for representing the brain functional connectivity. (3) Employing statistical techniques to scrutinize functional brain structures in Autism and Control subjects. (4) Implementing both autoencoder-based feature extraction and entire feature-based approach coupled with AI-based learning classifiers to predict Autism.
    Results: The ensemble classifier with the extracted feature set achieves a classification accuracy of 84.7% ± 0.3% using the MSDL atlas. Meanwhile, the 1D-CNN model, employing all features, exhibits superior classification accuracy of 88.6% ± 1.7% with the Smith 2009 (rsn70) atlas.
    Comparison with existing method (s): The proposed methodology outperforms the conventional correlation-based functional connectivity approach with a notably high prediction accuracy of more than 88%, whereas considering all direct and noisy indirect region-based functional connectivity, the traditional methods bound the prediction accuracy within 70% to 79%.
    Conclusions: This study underscores the potential of sparsity-based FC analysis using rs-fMRI data as a prognostic biomarker for detecting Autism.
    MeSH term(s) Humans ; Autistic Disorder/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Brain Mapping/methods ; Brain/diagnostic imaging ; Biomarkers ; Autism Spectrum Disorder/diagnostic imaging
    Chemical Substances Biomarkers
    Language English
    Publishing date 2024-02-29
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 282721-9
    ISSN 1872-678X ; 0165-0270
    ISSN (online) 1872-678X
    ISSN 0165-0270
    DOI 10.1016/j.jneumeth.2024.110100
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