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<p>Chronic renal disorder ranks among the top twenty leading causes of increasing morbidity and mortality on a global scale, impacting approximately 20% of the adult population. Chronic kidney disease (CKD) represents a condition characterized by the disruption of normal kidney function. The imperative need for precise diagnostic methods to promptly identify CKD arises from the rapid proliferation of patients afflicted by this ailment. Particularly in developing nations, where accurate diagnosis can be prohibitively expensive, CKD is often perceived as a potentially life-threatening condition. Consequently, early detection of CKD, aimed at safeguarding kidney health and decelerating its progression, has emerged as a paramount concern for the medical community. Within this disorder, the kidneys undergo impairment and lose their ability to effectively cleanse the blood as they typically do. Renal disease, by its nature, is a chronic ailment fraught with an escalating risk of deterioration over time. In this research paper, other supervised learning techniques, namely logistic regression, coupled with particle swarm optimization to discern significant features among the numerous parameters for disease identification.</p><p>.</p>

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Enhancing Chronic Kidney Disease Diagnosis with Modified Logistic Regression and Particle Swarm Optimization

  • 期刊论文

  • 发表日期：

    2025年6月19日

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  • Pawan Mishra,
  • Pooja,
  • Shashi Prakash Tripathi,
  • Vandana Rathore

摘要

Chronic renal disorder ranks among the top twenty leading causes of increasing morbidity and mortality on a global scale, impacting approximately 20% of the adult population. Chronic kidney disease (CKD) represents a condition characterized by the disruption of normal kidney function. The imperative need for precise diagnostic methods to promptly identify CKD arises from the rapid proliferation of patients afflicted by this ailment. Particularly in developing nations, where accurate diagnosis can be prohibitively expensive, CKD is often perceived as a potentially life-threatening condition. Consequently, early detection of CKD, aimed at safeguarding kidney health and decelerating its progression, has emerged as a paramount concern for the medical community. Within this disorder, the kidneys undergo impairment and lose their ability to effectively cleanse the blood as they typically do. Renal disease, by its nature, is a chronic ailment fraught with an escalating risk of deterioration over time. In this research paper, other supervised learning techniques, namely logistic regression, coupled with particle swarm optimization to discern significant features among the numerous parameters for disease identification.

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