Publications by authors named "Lara Alqahtani"
Sensors (Basel)
October 2024
Article Synopsis
- - The study focuses on using the YOLOv8 deep learning model to automate the grading of germinal matrix hemorrhage (GMH) in premature infants, diagnosed via cranial ultrasound.
- - A dataset of 586 infants' ultrasound images was analyzed, categorizing them into five grades of GMH: Normal, Grade 1, Grade 2, Grade 3, and Grade 4.
- - The YOLOv8 model performed exceptionally well with high accuracy rates, achieving a mean average precision of 0.979, which could improve diagnosis efficiency for radiologists.
