The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …

Purpose Our review of acute brain insult articles indicated that the patients' individual (i)
timeline panels with the defined time points since the emergency call and (ii) serial brain …

Background Patients suffered aneurysmal subarachnoid hemorrhage (aSAH) usually
develop poor survival and functional outcome. Evaluating aSAH patients at high risk of poor …

Brain diseases threaten hundreds of thousands of people over the world. Medical imaging
techniques such as MRI and CT are employed for various brain disease studies. As artificial …

Abstract Machine learning (ML) has revolutionized data processing in recent years. This
study presents the results of the first prediction models based on a long-term monocentric …

Subarachnoid hemorrhage (SAH) is one of the major health issues known to society and
has a higher mortality rate. The clinical factors with computed tomography (CT), magnetic …

Objective Machine learning (ML) models have been widely applied in stroke prediction,
diagnosis, treatment, and prognosis assessment. We aimed to conduct a comprehensive …

According to the Korea Institute for Health and Social Affairs, in 2017, the elderly, aged 65 or
older, had an average of 2.7 chronic diseases per person. The concern for the medical …

Early and reliable prediction of shunt-dependent hydrocephalus (SDHC) after aneurysmal
subarachnoid hemorrhage (aSAH) may decrease the duration of in-hospital stay and reduce …

The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …