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Related Experiment Video

Updated: Nov 14, 2025

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Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray.

P Menéndez Fernández-Miranda1,2, P Sanz Bellón3,4, A Pérez Del Barrio3,4

  • 1Departamento de Radiología, Hospital Universitario "Marqués de Valdecilla", Santander, Spain. pablomenendezfernandezmiranda@gmail.com.

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Summary

This study introduces COVID-19 TRAINING, a free web application designed to help medical professionals improve their skills in evaluating chest X-rays for coronavirus disease 2019 (COVID-19) diagnosis.

Keywords:
COVID‐19Chest X-rayDiagnostic accuracy valuesMedical applicationMedical educationTraining on diagnosis

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Area of Science:

  • Medical Imaging
  • Infectious Diseases
  • Artificial Intelligence in Medicine

Background:

  • The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, rapidly spread globally.
  • Accurate interpretation of chest X-rays (CXR) is crucial for managing COVID-19 patients, but can be challenging.
  • Existing training methods for CXR interpretation may not adequately prepare clinicians for COVID-19 specific findings.

Purpose of the Study:

  • To develop and evaluate a free web-based application, COVID-19 TRAINING, for enhancing the diagnostic accuracy of healthcare professionals in interpreting COVID-19 related chest X-rays.
  • To provide a structured training environment with immediate feedback on diagnostic performance metrics.
  • To assess the effectiveness of the application in improving user diagnostic accuracy, sensitivity, and specificity.

Main Methods:

  • Development of a web application, "COVID-19 TRAINING", featuring 196 chest X-rays categorized as non-pathological, COVID-19 positive, or other pathologies.
  • Users engaged in diagnostic training by classifying CXR images and received performance feedback.
  • Diagnostic accuracy, sensitivity, specificity, and global accuracy were calculated for each user.
  • Statistical analysis was performed to correlate user performance metrics and engagement levels.

Main Results:

  • The COVID-19 TRAINING application demonstrated average user diagnostic accuracy values of 0.72 for sensitivity, 0.64 for specificity, and 0.68 for global accuracy.
  • A significant inverse relationship was observed between sensitivity and specificity (p < 0.0001).
  • Higher user engagement, indicated by more submitted answers, correlated with improved overall diagnostic accuracy (p = 0.0002).

Conclusions:

  • The COVID-19 TRAINING application serves as an effective and accessible tool for medical professionals to acquire and refine skills in interpreting chest X-rays for COVID-19.
  • The application offers a novel method for evaluating diagnostic performance based on objective accuracy metrics.
  • This platform facilitates efficient data collection for research on diagnostic accuracy in medical professionals during public health crises.