Multicriteria decision support system for triage and ethical allocation of scarce resources to COVID-19 patients
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| Publicado en: | Multimedia Tools and Applications vol. 83, no. 9 (Mar 2024), p. 27463 |
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| Autor principal: | |
| Otros Autores: | |
| Publicado: |
Springer Nature B.V.
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 100 | 1 | |a Chandra, Tej Bahadur |u Bennett University, School of Computer Science Engineering and Techology, Greator Noida, India (GRID:grid.503009.f) (ISNI:0000 0004 6360 2252) | |
| 245 | 1 | |a Multicriteria decision support system for triage and ethical allocation of scarce resources to COVID-19 patients | |
| 260 | |b Springer Nature B.V. |c Mar 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Mitigating the rapid surge of Coronavirus disease (COVID-19) is one of the challenging tasks for the healthcare industry. While offering adequate healthcare services to the best of their ability, scarce medical resources like medicines, ICU beds, ventilators, test kits, personal protective equipment (PPE), domain experts, etc., forks an additional ethics dispute. To help with difficult triage decisions, developing appropriate triage protocols and rationing resources is of vital importance. In this paper, we proposed a multicriteria decision support system (MDSS) that performs weighted aggregation of different associated symptoms, clinical and radiological findings. The model assists physicians to priorities patients based on disease severity. In this study, 20 commonly used symptomatological, clinical and radiological variables were considered in addition to computer-aided diagnosis (CAD) system’s decision. Subsequently, the robustness of the proposed method is evaluated using a private dataset and compared with the results of subjective evaluation by domain experts. The obtained experimental results with positive correlation coefficient r = 0.9554 (between MDSS rank and ground-truth rank) and r = 0.8622 (between MDSS rank and computer-aided diagnosis (CAD) based rank) at 95% confidence interval confirm the strong agreement between proposed method and domain expert. The proposed system could be useful in low resource settings, specifically in pandemic situations and could also be updated to prioritize resources in completely new scenarios. | |
| 653 | |a Decision support systems | ||
| 653 | |a Multiple criterion | ||
| 653 | |a Health care | ||
| 653 | |a Computer aided decision processes | ||
| 653 | |a Signs and symptoms | ||
| 653 | |a Patients | ||
| 653 | |a Diagnosis | ||
| 653 | |a Subject specialists | ||
| 653 | |a Health services | ||
| 653 | |a Viral diseases | ||
| 653 | |a Ethics | ||
| 653 | |a Coronaviruses | ||
| 653 | |a Correlation coefficients | ||
| 653 | |a COVID-19 | ||
| 700 | 1 | |a Singh, Bikesh Kumar |u National Institute of Technology Raipur, Department of Biomedical Engineering, Raipur, India (GRID:grid.444688.2) (ISNI:0000 0004 1775 3076) | |
| 773 | 0 | |t Multimedia Tools and Applications |g vol. 83, no. 9 (Mar 2024), p. 27463 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2933268906/abstract/embedded/Q8Z64E4HU3OH5N8U?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2933268906/fulltextPDF/embedded/Q8Z64E4HU3OH5N8U?source=fedsrch |