Clinical decision support systems (CDSS) in assistance to COVID-19 diagnosis: A scoping review on types and evaluation methods

CONCLUSION: CDSS for COVID-19 diagnosis have been developed mainly through machine learning (ML) methods. The greater use of these techniques can be due to their availability of public data sets about chest imaging. Although these studies indicate high accuracy for CDSS based on ML, their novelty and data set biases raise questions about replacing these systems as clinician assistants in decision-making. Further studies are needed to improve and compare the robustness and reliability of nonknowledge-based and knowledge-based CDSS in COVID-19 diagnosis.PMID:38384976 | PMC:PMC10879639 | DOI:10.1002/hsr2.1919

Source: Rural Remote Health - February 22, 2024 Category: Rural Health Authors: Arefeh Ameri Atefeh Ameri Farzad Salmanizadeh Kambiz Bahaadinbeigy Source Type: research