PURPOSE: Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and study the impact of using this DLM on sample size requirements for neuroprotective trials.
Long COVID shares a number of clinical features with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), including post-exertional malaise, severe fatigue, and neurocognitive deficits. Utilizing validated assessment tools that accurately and...
PURPOSE: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance.
To evaluate the usefulness of robot-assisted total laparoscopic hysterectomy with four equally-spaced ports (RA-TLH/4e) without an assistant port. In RA-TLH/4e, four da Vinci ports were placed horizontally at a height of 4 cm above the umbilicus with...
BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) are at risk of sudden death, and individuals with ≥1 major risk markers are considered for primary prevention implantable cardioverter-defibrillators. Guidelines recommend cardiac magnetic r...
OBJECTIVE: We aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images.
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