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This chapter explores the transformative impact of artificial intelligence (AI) on the healthcare system, particularly in enhancing the accuracy, efficiency, and speed of disease diagnostics. A key advantage of AI integration in healthcare lies in its capacity to analyze vast amounts of medical data with unprecedented precision, enabling early disease detection and supporting proactive interventions. By comparing diagnostic results with extensive datasets, AI algorithms can identify early-stage or dormant conditions, such as suspicious tumors or lesions, which facilitates early intervention and reduces the risk of disease progression. Despite these advancements, challenges persist regarding data security and patient privacy, as well as the ethical application of algorithms in clinical practice. Effective AI implementation also requires thorough training of healthcare professionals to interpret AI-driven insights accurately. Nonetheless, AI-driven healthcare holds substantial potential for advancing patient care and expanding medical understanding. This chapter provides a comprehensive analysis of recent AI advancements in disease prediction and diagnostics, highlighting its essential role in the future of healthcare.

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Trends in AI for Disease and Diagnostic Prediction: A Healthcare Perspective

  • 章节

  • 发表日期：

    2025年

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  • Saurav Kumar Mishra,
  • Tabsum Chhetri,
  • Anagha Balakrishnan,
  • Sneha Roy,
  • Kusum Gurung,
  • J. Jeba Praba,
  • John J. Georrge

摘要

This chapter explores the transformative impact of artificial intelligence (AI) on the healthcare system, particularly in enhancing the accuracy, efficiency, and speed of disease diagnostics. A key advantage of AI integration in healthcare lies in its capacity to analyze vast amounts of medical data with unprecedented precision, enabling early disease detection and supporting proactive interventions. By comparing diagnostic results with extensive datasets, AI algorithms can identify early-stage or dormant conditions, such as suspicious tumors or lesions, which facilitates early intervention and reduces the risk of disease progression. Despite these advancements, challenges persist regarding data security and patient privacy, as well as the ethical application of algorithms in clinical practice. Effective AI implementation also requires thorough training of healthcare professionals to interpret AI-driven insights accurately. Nonetheless, AI-driven healthcare holds substantial potential for advancing patient care and expanding medical understanding. This chapter provides a comprehensive analysis of recent AI advancements in disease prediction and diagnostics, highlighting its essential role in the future of healthcare.