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This article explores the application of various deep-learning algorithms to predict anemia based on images of the palpebral conjunctiva. Anemia, a global health concern affecting millions, poses a significant public health risk. Leveraging deep learning in the medical domain, this research employs a successful model utilizing the Eyes-Defy-Anemia dataset. The blood vessels within the palpebral and fornical conjunctivae may reveal crucial information regarding a patient's overall health, including the presence of anemia. The study proposes a practical approach to developing a precise and cost-effective tool for anemia identification, with potential implications for significant advancements in public health.

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Classification of Anemia Disorder: A Comparative Analysis of CNN Model and Pre-trained Models

  • 会议论文

  • 发表日期：

    2026年

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  • K. S. Hemanth,
  • S. Nagaraju,
  • B. Muralidhara

摘要

This article explores the application of various deep-learning algorithms to predict anemia based on images of the palpebral conjunctiva. Anemia, a global health concern affecting millions, poses a significant public health risk. Leveraging deep learning in the medical domain, this research employs a successful model utilizing the Eyes-Defy-Anemia dataset. The blood vessels within the palpebral and fornical conjunctivae may reveal crucial information regarding a patient's overall health, including the presence of anemia. The study proposes a practical approach to developing a precise and cost-effective tool for anemia identification, with potential implications for significant advancements in public health.