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<p>Facilitating the pneumonia diagnosis for doctors is crucial task of saving lives of human beings. Artificial intelligence has been widely emerged in the medicine domain in which medical imaging gives informative data and provides a huge amount of details about patient’s health. Traditional methods of analyzing medical images may lead sometimes to false diagnosis because of image qualities or competence of doctors; therefore, looking for modern solutions is required. Machine learning algorithms proved their efficiency in different fields, but with the big amount of data provided by medical images, making the task somehow difficult. In our work, we have proposed selecting statistical parameters from patient X-rays image and using them in common machine learning models for pneumonia diagnosis. Selecting the images parameters is done by IBM SPSS tool, and verifying their significance is performed by SPSS Modeler, then the selected parameters are included in machine learning algorithms. Performances of classifying images are checked via accuracy metrics.</p>

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Efficient selection of statistical parameters for machine learning-based pneumonia diagnosis algorithms using SPSS modeler

  • 期刊论文

  • 发表日期：

    2025年10月7日

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  • Abdelhai Lati,
  • Badreddine Atallah,
  • Djalila Belkebir,
  • Ibtissem Lati

摘要

Facilitating the pneumonia diagnosis for doctors is crucial task of saving lives of human beings. Artificial intelligence has been widely emerged in the medicine domain in which medical imaging gives informative data and provides a huge amount of details about patient’s health. Traditional methods of analyzing medical images may lead sometimes to false diagnosis because of image qualities or competence of doctors; therefore, looking for modern solutions is required. Machine learning algorithms proved their efficiency in different fields, but with the big amount of data provided by medical images, making the task somehow difficult. In our work, we have proposed selecting statistical parameters from patient X-rays image and using them in common machine learning models for pneumonia diagnosis. Selecting the images parameters is done by IBM SPSS tool, and verifying their significance is performed by SPSS Modeler, then the selected parameters are included in machine learning algorithms. Performances of classifying images are checked via accuracy metrics.