The role of artificial intelligence in the diagnosis of keratoconus:
In keratoconus, the analogy of artificial intelligence to a "double-edged knife" is quite accurate and even bolder:
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🔹 AI maker edge in keratoconus
When AI is a tool to strengthen clinical decision-making:
• Early diagnosis (Subclinical / Forme Fruste)
Simultaneous analysis of topography, tomography, thickness and posterior elevation
What the human eye alone may miss
• Risk Stratification before refractive surgery
Reduction of patient selection error for LASIK / SMILE
Prevention of iatrogenic ectasia
• Progress monitoring Disease
Diagnosis of real progression against machine noise
• Advanced research
Discovery of different phenotypes of keratoconus and different responses to CXL
👉 Here AI is like a fine blade of microkratom in the hands of an experienced surgeon.
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🔻 The dangerous edge of AI in keratoconus
When AI replaces clinical judgement:
• False reassurance
"AI-normal" patient but with a history of severe rubbing or atopy
• Overdiagnosis
Labeling keratoconus to physiological thin corneas or post-LVC
• Ignoring the clinical background
Age, family history, asymmetric progress, patient behavior
• Machine treatment decisions
CXL based solely on score without understanding Biology of stroma
👉 Here is the edge that can make a healthy patient sick or deprive a real patient of timely treatment.
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🧠 short and professional summary
If you want to say in a scientific sentence:
In keratoconus, AI is a double-edged sword:
a powerful tool for early detection and risk stratification,
but dangerous when it replaces clinical judgment rather than augmenting it.
Or the more official Farsi version:
In keratoconus, artificial intelligence is a double-edged sword;
a powerful tool for early detection and risk assessment,
but dangerous if it replaces rather than complements clinical judgment.
