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<p>Machine learning is a rapidly evolving field of Artificial Intelligence, aimed at reshaping multiple domains—namely education, transportation, finance, e-commerce, and healthcare—by enabling data-driven learning to automate complex decisions. In healthcare, next-generation artificial intelligence–driven analytics has emerged as a prominent research area, aiming to deliver accurate, efficient, and intelligent diagnostic decisions at reduced cost while addressing the scalability and expense limitations of traditional methods. Ensuring timely and precise medical diagnosis remains a critical challenge in modern healthcare, particularly in the management of patients with critical conditions. This review highlights that the integration of swarm intelligence with machine learning significantly enhances the early disease diagnosis process by provides timely and precise decision support. As seen, traditional diagnostic systems, reliant on rule-based methods and manual interpretation, often suffer from limited scalability and suboptimal accuracy. In contrast, AI-driven smart diagnostics leverage computational techniques and integrated approaches to effectively address these challenges, thereby enabling more precise and reliable outcomes. Hence, by utilizing the integrated approach of swarm intelligence and machine learning enhances healthcare diagnostics through early detection, improved accuracy, and intelligent decision support. This synergy holds strong potential for advancing AI-based healthcare solutions with robust and better data-driven outcomes.</p>

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A Comprehensive Review on Swarm Intelligence and Machine Learning Based Diagnostic Techniques for Automated Disease Diagnosis

  • 期刊论文

  • 发表日期：

    2026年4月14日

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  • Rimmy Chuchra,
  • Manik Sharma,
  • Sanjeev Kumar Sharma

摘要

Machine learning is a rapidly evolving field of Artificial Intelligence, aimed at reshaping multiple domains—namely education, transportation, finance, e-commerce, and healthcare—by enabling data-driven learning to automate complex decisions. In healthcare, next-generation artificial intelligence–driven analytics has emerged as a prominent research area, aiming to deliver accurate, efficient, and intelligent diagnostic decisions at reduced cost while addressing the scalability and expense limitations of traditional methods. Ensuring timely and precise medical diagnosis remains a critical challenge in modern healthcare, particularly in the management of patients with critical conditions. This review highlights that the integration of swarm intelligence with machine learning significantly enhances the early disease diagnosis process by provides timely and precise decision support. As seen, traditional diagnostic systems, reliant on rule-based methods and manual interpretation, often suffer from limited scalability and suboptimal accuracy. In contrast, AI-driven smart diagnostics leverage computational techniques and integrated approaches to effectively address these challenges, thereby enabling more precise and reliable outcomes. Hence, by utilizing the integrated approach of swarm intelligence and machine learning enhances healthcare diagnostics through early detection, improved accuracy, and intelligent decision support. This synergy holds strong potential for advancing AI-based healthcare solutions with robust and better data-driven outcomes.