Advanced real-time detection of acute ischemic stroke using YOLOv12, YOLOv11, and YOLO-NAS: a comparative study for multi-class classification

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September 15, 2025Scientific ReportsOpen Access

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Key Points

YOLOv11 achieved the highest mean average precision at IoU 0.5 (98.5%), indicating it is the most reliable model for multi-class ischemic stroke detection.
The study utilized a dataset with four categories for acute ischemic stroke detection, implementing thorough preprocessing and evaluation protocols.
YOLOv12 performed similarly to YOLOv11 but with slightly lower speed, while YOLO-NAS demonstrated the fastest detection at 154 frames per second.
Results showcase the critical balance between detection accuracy and processing speed, essential for timely intervention in emergency stroke care.

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Comparative evaluation of YOLOv12, YOLOv11, and YOLO-NAS for detecting acute ischemic stroke, highlighting accuracy and speed trade-offs.

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El-Geneedy et al. (2025) studied this question.

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