Global Perspectives on Myopia—Epidemiology, Pathophysiology, and Emerging Assessment Technologies

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 595

Special Issue Editor


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Guest Editor
1. Department of Ophthalmology, Chung-Ang University, College of Medicine, Seoul, Republic of Korea
2. Department of Ophthalmology, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong-si, Republic of Korea
Interests: ophthalmology; neuroophthalmology; optic neuropathy

Special Issue Information

Dear Colleagues,

Myopia has become a major global public health concern, with its prevalence rising sharply in recent decades, particularly in East Asia. It is now one of the leading causes of visual impairment worldwide. High myopia is associated with sight-threatening complications such as retinal detachment, myopic maculopathy, and glaucoma, placing a significant burden on individuals and healthcare systems and underscoring the urgent need for early detection and accurate diagnostic strategies.

This Special Issue will provide a concise yet comprehensive overview of the current state of myopia research and clinical practice. It will include a comprehensive summary of epidemiological trends, pathophysiological mechanisms, and innovative diagnostic approaches. We will highlight emerging technologies such as advanced imaging modalities (e.g., OCT, AI-based screening tools), biomarker discovery, and digital diagnostic platforms to enhance early detection and risk stratification.

The core focus of this Special Issue will comprise clinical research studies conducted in different countries, offering a global perspective on strategies to manage or prevent myopia progression or myopia development. By presenting diverse findings and approaches, we aim to improve diagnostic precision, facilitate early intervention, and inform public health strategies for myopia management.

We invite contributions that explore novel diagnostic tools, validation studies, and translational research to advance this field. Through this Special Issue, we hope to offer meaningful insights for clinicians, researchers, and public health professionals involved in the global fight against myopia.

Dr. Ungsoo-Samuel Kim
Guest Editor

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Keywords

  • myopia
  • diagnostic imaging
  • optical coherence tomography (OCT)
  • artificial intelligence (AI)
  • biomarkers
  • early detection
  • prevention
  • epidemiology
  • digital diagnostics

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Published Papers (1 paper)

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Research

13 pages, 1357 KB  
Article
Decision Tree Modeling to Predict Myopia Progression in Children Treated with Atropine: Toward Precision Ophthalmology
by Jun-Wei Chen, Chi-Jie Lu, Chieh-Han Yu, Tzu-Chi Liu and Tzu-En Wu
Diagnostics 2025, 15(16), 2096; https://doi.org/10.3390/diagnostics15162096 - 20 Aug 2025
Viewed by 444
Abstract
Background/Objectives: Myopia is a growing global health concern, especially among school-aged children in East Asia. Topical atropine is a key treatment for pediatric myopia control, but individual responses vary, with some children showing rapid progression despite higher doses. This retrospective observational study [...] Read more.
Background/Objectives: Myopia is a growing global health concern, especially among school-aged children in East Asia. Topical atropine is a key treatment for pediatric myopia control, but individual responses vary, with some children showing rapid progression despite higher doses. This retrospective observational study aims to develop an interpretable machine learning model to predict individualized treatment responses and support personalized clinical decisions, based on data collected over a 3-year period without a control group. Methods: A total of 1545 pediatric eyes treated with topical atropine for myopia control at a single tertiary medical center are analyzed. Classification and regression tree (CART) is constructed to predict changes in spherical equivalent (SE) and identify influencing risk factors. These factors are mainly received treatments for myopia including atropine dosage records, treatment duration, and ophthalmic examinations. Furthermore, decision rules that closely resemble the clinical diagnosis process are provided to assist clinicians with more interpretable insights into personalized treatment decisions. The performance of CART is evaluated by comparing with the benchmark model of least absolute shrinkage and selection operator regression (Lasso) to confirm the practicality of CART usage. Results: Both the CART and Lasso models demonstrated comparable predictive performance. The CART model identified baseline SE as the primary determinant of myopia progression. Children with a baseline SE more negative than −3.125 D exhibited greater myopic progression, particularly those with prolonged treatment duration and higher cumulative atropine dosage. Conclusions: Baseline SE has been identified as the key factor affecting SE difference. The generated decision rules from CART demonstrate the use of explainable machine learning in precision myopia management. Full article
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