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Saisakul Chernbumroong

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IEEE Journal of Biomedical and Health Informatics|April 29, 2014
Genetic algorithm-based classifiers fusion for multisensor activity recognition of elderly peopleSaisakul Chernbumroong, Shuang Cang, Hongnian Yu
Emergency Medicine Journal : EMJ|October 28, 2021
Comparative analysis of major incident triage tools in children: a UK population-based analysisJames Vassallo, Saisakul Chernbumroong, Nabeela Malik, et al.
The European Respiratory Journal|December 11, 2020
Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosisSaisakul Chernbumroong, Janice Johnson, Nishant Gupta, et al.
European Journal of Nutrition|November 9, 2021
Metabotypes of flavan-3-ol colonic metabolites after cranberry intake: elucidation and statistical approachesPedro Mena, Claudia Favari, Animesh Acharjee, et al.
Emergency Medicine Journal : EMJ|September 26, 2023
Triage in major incidents: development and external validation of novel machine learning-derived primary and secondary triage toolsYuanwei Xu, Nabeela Malik, Saisakul Chernbumroong, et al.
Eclinicalmedicine|April 18, 2020
Violence-related knife injuries in a UK city; epidemiology and impact on secondary care resourcesNabeela S Malik, Beau Munoz, Cynthia de Courcey, et al.
Eclinicalmedicine|July 26, 2021
The BCD Triage Sieve outperforms all existing major incident triage tools: Comparative analysis using the UK national trauma registry populationNabeela S Malik, Saisakul Chernbumroong, Yuanwei Xu, et al.
Eclinicalmedicine|November 8, 2021
Paediatric major incident triage: UK military tool offers best performance in predicting the need for time-critical major surgical and resuscitative interventionNabeela S Malik, Saisakul Chernbumroong, Yuanwei Xu, et al.
European Heart Journal|January 11, 2023
Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcareSimrat K Gill, Andreas Karwath, Hae-Won Uh, et al.
Lancet (London, England)|September 2, 2021
Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysisAndreas Karwath, Karina V Bunting, Simrat K Gill, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Journal of Biomedical and Health Informatics|April 29, 2014
Genetic algorithm-based classifiers fusion for multisensor activity recognition of elderly peopleSaisakul Chernbumroong, Shuang Cang, Hongnian Yu
Emergency Medicine Journal : EMJ|October 28, 2021
Comparative analysis of major incident triage tools in children: a UK population-based analysisJames Vassallo, Saisakul Chernbumroong, Nabeela Malik, et al.
The European Respiratory Journal|December 11, 2020
Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosisSaisakul Chernbumroong, Janice Johnson, Nishant Gupta, et al.
European Journal of Nutrition|November 9, 2021
Metabotypes of flavan-3-ol colonic metabolites after cranberry intake: elucidation and statistical approachesPedro Mena, Claudia Favari, Animesh Acharjee, et al.
Emergency Medicine Journal : EMJ|September 26, 2023
Triage in major incidents: development and external validation of novel machine learning-derived primary and secondary triage toolsYuanwei Xu, Nabeela Malik, Saisakul Chernbumroong, et al.
Eclinicalmedicine|April 18, 2020
Violence-related knife injuries in a UK city; epidemiology and impact on secondary care resourcesNabeela S Malik, Beau Munoz, Cynthia de Courcey, et al.
Eclinicalmedicine|July 26, 2021
The BCD Triage Sieve outperforms all existing major incident triage tools: Comparative analysis using the UK national trauma registry populationNabeela S Malik, Saisakul Chernbumroong, Yuanwei Xu, et al.
Eclinicalmedicine|November 8, 2021
Paediatric major incident triage: UK military tool offers best performance in predicting the need for time-critical major surgical and resuscitative interventionNabeela S Malik, Saisakul Chernbumroong, Yuanwei Xu, et al.
European Heart Journal|January 11, 2023
Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcareSimrat K Gill, Andreas Karwath, Hae-Won Uh, et al.
Lancet (London, England)|September 2, 2021
Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysisAndreas Karwath, Karina V Bunting, Simrat K Gill, et al.
Pageof 1