Publications by authors named "Jianjun Chai"
Hemorrhage expansion (HE) is a common and serious condition in patients with intracerebral hemorrhage (ICH). In contrast to the volume changes, little is known about the morphological changes that occur during HE. We developed a novel method to explore the patterns of morphological change and investigate the clinical significance of this change in ICH patients.
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- About one-third of patients with spontaneous intracerebral hemorrhage don't know when their symptoms began, which limits research on time-sensitive treatments for these cases.
- The study introduces an artificial intelligence model that uses weakly supervised multitask learning (WS-MTL) to estimate the onset time of symptoms from non-contrast CT scans, aiming to assist clinicians in treating unclear-onset patients.
- With a dataset of 4004 patients and 10,780 CT scans, the WS-MTL model demonstrated high accuracy in classifications and satisfactory results in estimating onset time, suggesting it could be integrated into clinical practice for better treatment outcomes.
Article Synopsis
- * AEEG detected abnormal brain activity in 80% of patients, compared to 65% with REEG, and AEEG was significantly better at identifying epileptiform discharges (42.5% vs. 6.3%).
- * Patients monitored with AEEG had shorter hospital stays and fewer severe illness outcomes compared to those assessed with REEG, demonstrating AEEG's higher sensitivity and significance for clinical prognosis.