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Anemia continues to be one of the most prevalent global health challenges, affecting nearly one-fourth of the world’s population. Despite remarkable advances in anemia diagnosis, conventional hematological diagnostic approaches are based solely on hemoglobin levels and red cell indices and often fail to reveal complex or overlapping etiologies. The integration of artificial intelligence (AI) with multimodal data fusion marks a paradigm shift in precision of anemia diagnosis and management. This chapter explores the emergence of fusion intelligence consolidating demographic, clinical, hematological, biochemical, imaging, and genomic data to enhance the accuracy of anemia diagnosis and management. Emphasis is placed on clinical applications, ethical considerations, and translational challenges. By unifying diverse large data sources into an explainable and equitable AI ecosystem, fusion intelligence redefines anemia care from reactive correction to proactive prevention, laying the foundation for patient-centered, data-driven hematology.

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Fusion Intelligence for Anemia Diagnosis: Multimodal AI Approaches for Early Detection and Integrated Management

  • 章节

  • 发表日期：

    2026年

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  • Raj Kishore Singh,
  • Rujal Raj Singh,
  • Aradhana Singh,
  • J. P. Pandey,
  • Abhinav K. Gautam

摘要

Anemia continues to be one of the most prevalent global health challenges, affecting nearly one-fourth of the world’s population. Despite remarkable advances in anemia diagnosis, conventional hematological diagnostic approaches are based solely on hemoglobin levels and red cell indices and often fail to reveal complex or overlapping etiologies. The integration of artificial intelligence (AI) with multimodal data fusion marks a paradigm shift in precision of anemia diagnosis and management. This chapter explores the emergence of fusion intelligence consolidating demographic, clinical, hematological, biochemical, imaging, and genomic data to enhance the accuracy of anemia diagnosis and management. Emphasis is placed on clinical applications, ethical considerations, and translational challenges. By unifying diverse large data sources into an explainable and equitable AI ecosystem, fusion intelligence redefines anemia care from reactive correction to proactive prevention, laying the foundation for patient-centered, data-driven hematology.