What question did this study set out to answer?

To assess the role of artificial intelligence in the detection and grading of cataracts using color fundus photographs.

May 8, 2026Open Access

Role of artificial intelligence in detecting and grading cataracts using color fundus photographs: A systematic review and meta-analysis

Key Points

To assess the role of artificial intelligence in the detection and grading of cataracts using color fundus photographs.
Conducted a systematic review and meta-analysis of existing studies on AI and cataracts.
Included studies that utilized color fundus photographs for cataract detection and grading.
Analyzed the performance metrics of AI systems in detecting cataracts.
AI demonstrated high accuracy in cataract detection, with sensitivity rates exceeding 90%.
Grading accuracy using AI was consistent with human experts, achieving a kappa coefficient of 0.85 (95% CI 0.70-1.00).
P-values indicated significant differences in detection times favoring AI over traditional methods (p<0.01).

Abstract

Background: Cataracts are a leading cause of blindness and visual impairment worldwide, affecting millions of people. Early detection and accurate grading of cataracts are critical for timely intervention and improving patient outcomes. Artificial intelligence (AI), particularly deep learning, has emerged as a powerful tool for automating the detection and grading of cataracts using color fundus photographs.

Role of artificial intelligence in detecting and grading cataracts using color fundus photographs: A systematic review and meta-analysis

Key Points

Abstract

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