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A new Covid-19 diagnosis strategy using a modified KNN classifier.

Asmaa H Rabie1, Alaa M Mohamed2, M A Abo-Elsoud3

  • 1Computers and Control Department Faculty of Engineering, Mansoura University, Mansoura, Egypt.

Neural Computing & Applications
|June 26, 2023
PubMed
Summary

A new Covid-19 diagnostic strategy (CDS) uses enhanced gray wolf optimization (EGWO) for feature selection and a hybrid diagnosis methodology (HDM) for accurate detection. This approach significantly improves diagnostic performance for Covid-19 patients.

Keywords:
BGWOCovid-19DiagnosisFeature selectionKNNNB

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Area of Science:

  • Medical Diagnostics
  • Computational Biology
  • Machine Learning in Healthcare

Background:

  • The rapid global spread of Covid-19 necessitates accurate and timely diagnostic tools.
  • The lack of a universally effective vaccine underscores the importance of precise case identification and isolation.
  • Existing diagnostic methods may require improvement in speed and accuracy to combat the pandemic effectively.

Purpose of the Study:

  • To introduce a novel Covid-19 diagnostic strategy (CDS) for enhanced accuracy and speed.
  • To develop a two-phase strategy involving feature selection and a hybrid diagnostic methodology.
  • To improve the identification and isolation of Covid-19 infected individuals.

Main Methods:

  • Feature Selection Phase (FSP): Utilizes enhanced gray wolf optimization (EGWO), combining filter and wrapper techniques (FS and BGWO), to identify optimal laboratory test features for Covid-19.
  • Diagnosis Phase (DP): Employs a hybrid diagnosis methodology (HDM) comprising a weighting patient phase (WP²) using Naïve Bayes (NB) and a diagnostic patient phase (DP²) using K-nearest neighbor (KNN).
  • EGWO integrates filter methods with binary gray wolf optimization (BGWO) for robust feature selection.

Main Results:

  • The proposed Covid-19 diagnostic strategy (CDS) achieved high performance metrics.
  • Accuracy reached 99%, precision 88%, recall (sensitivity) 90%, and F-measure 91%.
  • Experimental results demonstrate the superiority of CDS over other diagnostic strategies.

Conclusions:

  • The developed Covid-19 diagnostic strategy (CDS) offers a rapid and highly accurate method for disease detection.
  • The combination of EGWO for feature selection and HDM for diagnosis proves effective.
  • This strategy holds significant potential for improving clinical decision-making and pandemic control.