Translational vision science & technology
May 1, 2025
PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis and management. The ability to accurately digitize VF reports is critical for maximizing the utility...
In the era of rapid societal modernization, the issue of crime stands as an intrinsic facet, demanding our attention and consideration. As our communities evolve and adopt technological advancements, the dynamic landscape of criminal activities becom...
BACKGROUND: To compare liver image quality and lesion detection using an AI-augmented T1-weighted sequence on hepatobiliary-phase gadoxetate-enhanced magnetic resonance imaging (MRI).
Parkinson's disease (PD) remains a condition without a cure, though its early manifestations can be managed effectively by medical professionals. This underscores the significance of early detection of PD. It has been widely demonstrated that handwri...
BACKGROUND: Accurate diagnosis of neuroendocrine neoplasms (NENs) is challenging, especially in poorly differentiated neuroendocrine carcinomas (NECs). This study was aimed to search the best or best combination of neuroendocrine markers in the diagn...
Foundation models prepare neural networks for applications in specific domains, such as speech applications or image analysis, through self-supervised pretraining. These models can be adapted for specific applications, such as histopathological diagn...
International journal of neural systems
May 1, 2025
Epilepsy is a prevalent neurological disorder characterized by recurrent seizures, which are sudden bursts of electrical activity in the brain. The Epileptor model is a computational model specifically created to replicate the complex dynamics of epi...
This study develops a comprehensive framework that integrates computational fluid dynamics (CFD) and machine learning (ML) to predict milk flow behavior in lactating breasts. Utilizing CFD and other high-fidelity simulation techniques to tackle fluid...
OBJECTIVES: To validate the accuracy and reliability of a graph convolutional network (GCN)-based superimposition method of a maxillary digital dental model (MDM) by comparing it with manual superimposition and quantifying the clinical error from thi...
OBJECTIVES: This study evaluated the accuracy and reliability of deep learning-based segmentation techniques for mandibular canal identification in cone-beam CT (CBCT) data to provide a reliable and efficient support tool for dental implant treatment...
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