Application of deep learning models for detection of subdural hematoma: a systematic review and meta-analysis
Author:
Funder
Engineering and Physical Sciences Research Council
Wellcome Trust
Publisher
BMJ
Subject
Neurology (clinical),General Medicine,Surgery
Reference16 articles.
1. Abdollahifard S , Farrokhi A , Mowla A . Application of deep learning models for detection of subdural hematoma: a systematic review and meta-analysis. J Neurointerv Surg 2022:jnis-2022-019627. doi:10.1136/jnis-2022-019627
2. Deep learning models for triaging hospital head MRI examinations;Wood;Med Image Anal,2022
3. Farzaneh N , Williamson CA , Jiang C , et al . Automated segmentation and severity analysis of subdural hematoma for patients with traumatic brain injuries. Diagnostics (Basel) 2020;10:773. doi:10.3390/diagnostics10100773
4. Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model;Inkeaw;Comput Biol Med,2022
5. Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models
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1. Optimising brain age estimation through transfer learning: A suite of pre‐trained foundation models for improved performance and generalisability in a clinical setting;Human Brain Mapping;2024-03
2. Response to ‘Application of deep learning models for detection of subdural hematoma: a systematic review and meta-analysis’;Journal of NeuroInterventional Surgery;2023-09-15
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