… We developed deep learning algorithms to separately detect as many as nine critical
findings on head CT scans. We described the use of deep learning for detection of calvarial …

… In recent years, the performance of deep learning (DL) algorithms on various medical
image tasks have continually improved. DL algorithms have been proposed as a tool to detect …

… deep learning framework for detecting clinically-relevant abnormalities in minimally processed,
hospital-grade axial T2-weighted and axial diffusion-weighted head … for use with the MRI …

… of deep learning (DL) techniques, and the extensive use of Deep Neural Networks. In this
article, we shall do a review of the topic from the distinctive perspective of deep learning, …

… However, the existing HaN-related deep learning-based methods either use sliding
windows working on patches that cannot capture global features or rely on atlas registration to …

… deep learning algorithms can accurately identify head CT scan abnormalities requiring urgent
attention. This opens up the possibility to use … the accurate use of deep learning algorithms …

… In J–L, the SDH is detected despite its isodensity to gray matter, showing that the deep
learning algorithm does not rely solely on hyperdensity but also uses other features to identify …

… deep learning models for classifying non-English head CT … For the specific labeling use case,
BOW and deep learning … , deep learning methods outperformed the machine learning BOW …

… , we can use head pose datasets to aid our head pose estimation and use fixed-head gaze
… Given those previous studies and the success of deep learning, we use deep CNNs for …

… We use a novel deep CNN framework on the same cohort of patients, improving on a … of
limited size, one uses a methodology called transfer learning. In transfer learning, a network that …