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Research Article: Using Radiomics and Convolutional Neural Networks for the Prediction of Hematoma Expansion After Intracerebral Hemorrhage

Date Published: 2023-08-09

Abstract:
Non-traumatic intracerebral hemorrhage (ICH) caused by rupture of arteries, veins, and capillaries, is becoming one of the main neurological diseases leading to death and disability in adults. It has been demonstrated that patients diagnosed with ICH, despite being conscious in their initial presentation, may experience a poor outcome or even fatality in their subsequent stages. Surgical intervention is usually required for critically ill patients. However, various complications may arise after craniotomy, such as infection, epilepsy, peptic ulcer, deep vein thrombosis et al. These complications may in turn accelerate the deterioration of patients’ health, ultimately leading to death, primarily among elderly patients., Prior research has identified a group of independent risk factors that can predict a poor prognosis of ICH, such as the patient’s age, Glasgow coma scale score, hematoma volume, hematoma enlargement (HE), and ventricular penetration.– Among these factors, HE, which mainly occurs within hours after the initial hemorrhage,, is the only factor that can be prevented after the patient is admitted to the hospital. Accordingly, exploring radiological signs for HE has become a research focus in recent years for radiologists.–

Introduction:
Non-traumatic intracerebral hemorrhage (ICH) caused by rupture of arteries, veins, and capillaries, is becoming one of the main neurological diseases leading to death and disability in adults. It has been demonstrated that patients diagnosed with ICH, despite being conscious in their initial presentation, may experience a poor outcome or even fatality in their subsequent stages. Surgical intervention is usually required for critically ill patients. However, various complications may arise after craniotomy, such as…

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