Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Mar 1, 2025
Date Accepted: Mar 31, 2025
Title: The Anemia Risk Warning Model Based on a Non-invasive Method: Key Insights and Clarifications
ABSTRACT
We recently read with great interest the paper by Zhang and colleagues [1], which presents a study on a non-invasive technique for diagnosing anemia using facial visible light reflectance spectroscopy, in combination with machine learning (ML) algorithms for predictive modeling. Anemia is a widespread public health issue affecting over 1.7 billion people, with symptoms including fatigue and cognitive decline [2]. The study focuses on utilizing facial spectral data to develop a risk warning model for anemia, providing a reliable alternative to conventional methods and holding promise for future clinical applications in non-invasive anemia diagnosis. Having closely reviewed the article, we would like to recommend some insights and clarifications to enhance the robustness of the results.
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