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Identifying vitamin deficiencies is one component of preventive healthcare. This end to end machine learning approach is a known technique, however, there is little to no mathematics involved in following this model to get the classification accuracy needed. This indicates that future research work aims to improve the present classification accuracy of vitamin deficiency particularly through the application of state-of-the-art neural network paradigms such as artificial neural networks (ANNs), convolutional neural networks (CNNs), and mobile nets. Using scans of their teeth, skin, and nails, this app helps users detect possible vitamin deficiencies without the need for blood tests. It also recommends a healthy diet to help redress the shortfall. As CNN mobile nets can generalize and learn significant samples and features on picture data, the human feature symbolization has become outdated.

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Analysis of a Deep Learning-Based, Accurate, and Efficient Technique for Vitamin Deficiency Detection in Customized Health Care System

  • 会议论文

  • 发表日期：

    2026年

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  • S. Kirubakaran,
  • Banothu Ramji,
  • B. Divya,
  • Nakeertha Rajkumar,
  • Ramya Paneerselvam

摘要

Identifying vitamin deficiencies is one component of preventive healthcare. This end to end machine learning approach is a known technique, however, there is little to no mathematics involved in following this model to get the classification accuracy needed. This indicates that future research work aims to improve the present classification accuracy of vitamin deficiency particularly through the application of state-of-the-art neural network paradigms such as artificial neural networks (ANNs), convolutional neural networks (CNNs), and mobile nets. Using scans of their teeth, skin, and nails, this app helps users detect possible vitamin deficiencies without the need for blood tests. It also recommends a healthy diet to help redress the shortfall. As CNN mobile nets can generalize and learn significant samples and features on picture data, the human feature symbolization has become outdated.