Study Data from Imam Abdulrahman Bin Faisal University Update Knowledge of Sensor Research (Deep Learning Approaches for the Assessment of Germinal Matrix Hemorrhage Using Neonatal Head Ultrasound).

Předmět:	INFORMATION technology PREMATURE infants ULTRASONIC imaging NEWSPAPER editors DEEP learning
Zdroj:	Health & Medicine Week; 11/22/2024, p6619-6619, 1p
Abstrakt:	Researchers at Imam Abdulrahman Bin Faisal University in Saudi Arabia have developed a deep learning approach using the YOLOv8 model to assess Germinal Matrix Hemorrhage (GMH) in premature infants through neonatal head ultrasound imaging. By analyzing a dataset of 586 infants, the model classified ultrasound images into five categories, achieving high accuracy and efficiency in GMH diagnosis. This study highlights the potential of deep learning technology to support radiologists in clinical settings and improve the diagnosis of critical conditions in premature infants. [Extracted from the article]
Databáze:	Complementary Index
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