BACKGROUND: Large language model (LLM)-linked chatbots may be an efficient source of clinical recommendations for healthcare providers and patients. This study evaluated the performance of LLM-linked chatbots in providing recommendations for the surg...
Exposure to hexavalent chromium damages genetic materials like DNA and chromosomes, further elevating cancer risk, yet research rarely focuses on related immunological mechanisms, which play an important role in the occurrence and development of canc...
Journal of imaging informatics in medicine
Apr 16, 2024
Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the d...
PURPOSE: To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction.
The diagnostic accuracy of cystoscopy varies according to the knowledge and experience of the performing physician. In this study, we evaluated the difference in cystoscopic gaze location patterns between medical students and urologists and assessed...
Segmentation of cerebral vasculature on MR vascular images is of great significance for clinical application and research. However, the existing cerebrovascular segmentation approaches are limited due to insufficient image contrast and complicated al...
PURPOSE: Patients with spinal cord injuries (SCIs) experience variable urinary symptoms and quality of life (QOL). Our objective was to use machine learning to identify bladder-relevant phenotypes after SCI and assess their association with urinary s...
OBJECTIVE: This study aimed to evaluate the usability of morphometric features obtained from mandibular panoramic radiographs in gender determination using machine learning algorithms.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 16, 2024
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...
PURPOSE: With the slice thickness routinely used in elbow MRI, small or subtle lesions may be overlooked or misinterpreted as insignificant. To compare 1 mm slice thickness MRI (1 mm MRI) with deep learning reconstruction (DLR) to 3 mm slice thicknes...
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