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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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An online platform for COVID-19 diagnostic screening using a machine learning algorithm.

Erito Marques de Souza Filho1, Rodrigo de Souza Tavares1, Bruno José Dembogurski1

  • 1Universidade Federal Rural do Rio de Janeiro - Nova Iguaçu (RJ), Brazil.

Revista Da Associacao Medica Brasileira (1992)
|April 19, 2023
PubMed
Summary
This summary is machine-generated.

This study developed an online machine learning tool to assess COVID-19 probability using clinical data. The innovative digital platform showed high user satisfaction, demonstrating the potential of AI in telemedicine.

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Area of Science:

  • Public Health
  • Digital Health
  • Machine Learning Applications

Background:

  • The COVID-19 pandemic presented significant public health challenges requiring innovative solutions.
  • Digital tools and artificial intelligence emerged as crucial components in managing the health crisis.
  • Telemedicine adoption accelerated, necessitating advanced diagnostic support systems.

Purpose of the Study:

  • To develop and evaluate a machine learning-based screening algorithm for COVID-19 diagnosis probability.
  • To create an accessible online platform integrating the algorithm for use in teleconsultations.
  • To assess user satisfaction and the effectiveness of the digital tool during the pandemic.

Main Methods:

  • Development of a machine learning risk model using clinical data.
  • Creation of an online platform for user data input.
  • Deployment and utilization of the platform in teleconsultation settings during the pandemic.

Main Results:

  • The online platform recorded 4,722 accesses and facilitated 126 teleconsultations.
  • High user satisfaction was reported, with an average rating above 4.8/5 and a Net Promoter Score of 94.4.
  • A response rate of 84.92% was achieved for satisfaction surveys.

Conclusions:

  • This represents the first online application using machine learning for probabilistic COVID-19 assessment based solely on user symptoms and clinical data.
  • The developed tool demonstrated significant user satisfaction and high engagement.
  • Integrating machine learning into telemedicine offers substantial potential for enhancing diagnostic capabilities and patient care.