AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Hematoma

Showing 31 to 40 of 48 articles

Clear Filters

Association of baseline hematoma and edema volumes with one-year outcome and long-term survival after spontaneous intracerebral hemorrhage: A community-based inception cohort study.

International journal of stroke : official journal of the International Stroke Society
BACKGROUND: Hospital-based studies have reported variable associations between outcome after spontaneous intracerebral hemorrhage and peri-hematomal edema volume.

Robot-Assisted Instrumented Fusion of a T8-9 Extension Distraction Fracture and Epidural Hematoma Evacuation: 2-Dimensional Operative Video.

Operative neurosurgery (Hagerstown, Md.)
The utilization of robotics has been gaining increased popularity in spine surgery. It can be used to assist in pedicle screw insertion when anatomy is complex in deformity surgery, but is also helpful in degenerative spine as it can minimize tissue ...

Deep learning for automatically predicting early haematoma expansion in Chinese patients.

Stroke and vascular neurology
BACKGROUND AND PURPOSE: Early haematoma expansion is determinative in predicting outcome of intracerebral haemorrhage (ICH) patients. The aims of this study are to develop a novel prediction model for haematoma expansion by applying deep learning mod...

A Robust Deep Learning Segmentation Method for Hematoma Volumetric Detection in Intracerebral Hemorrhage.

Stroke
BACKGROUND AND PURPOSE: Hematoma volume (HV) is a significant diagnosis for determining the clinical stage and therapeutic approach for intracerebral hemorrhage (ICH). The aim of this study is to develop a robust deep learning segmentation method for...

Weakly supervised multitask learning models to identify symptom onset time of unclear-onset intracerebral hemorrhage.

International journal of stroke : official journal of the International Stroke Society
BACKGROUND: Approximately one-third of spontaneous intracerebral hemorrhage patients did not know the onset time and were excluded from studies about time-dependent treatments for hyperacute spontaneous intracerebral hemorrhage.

An Early Warning System Using Machine Learning for the Detection of Intracranial Hematomas in the Emergency Trauma Setting.

Turkish neurosurgery
AIM: To present an early warning system (EWS) that employs a supervised machine learning algorithm for the rapid detection of extra-axial hematomas (EAHs) in an emergency trauma setting.

Advances in computed tomography-based prognostic methods for intracerebral hemorrhage.

Neurosurgical review
Spontaneous intracerebral hemorrhage (ICH) has high morbidity and mortality. Computed tomography (CT) plays an important role in the diagnosis, treatment, and research of cerebrovascular diseases. Non-contrast CT is widely used in the clinical diagno...

External validation study on the value of deep learning algorithm for the prediction of hematoma expansion from noncontrast CT scans.

BMC medical imaging
BACKGROUND: Hematoma expansion is an independent predictor of patient outcome and mortality. The early diagnosis of hematoma expansion is crucial for selecting clinical treatment options. This study aims to explore the value of a deep learning algori...

Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation.

IEEE journal of biomedical and health informatics
Accurate segmentation of the Intracranial Hemorrhage (ICH) in non-contrast CT images is significant for computer-aided diagnosis. Although existing methods have achieved remarkable 1 1 The code will be available from https://github.com/JohnleeHIT/SLE...