Purpose: This study aims to validate and revise the Spot Vision Screener referral criteria for detecting amblyopia risk factors (ARFs), visually significant refractive error (VSRE), and amblyopia.
Methods: In clinics, we gathered data from children aged 12 months to 7 years. The validity of the cut-off values was assessed using receiver operating characteristic (ROC) curves, with cycloplegic retinoscopy serving as a reference.
Objective: This study constructed a new conditional generative adversarial network (CGAN) model to predict changes in lateral appearance following orthodontic treatment.
Methods: Lateral cephalometric radiographs of adult patients were obtained before (T1) and after (T2) orthodontic treatment. The expanded dataset was divided into training, validation, and test sets by random sampling in a ratio of 8:1:1.
As combination therapy becomes more common in clinical applications, predicting adverse effects of combination medications is a challenging task. However, there are three limitations of the existing prediction models. First, they rely on a single view of the drug and cannot fully utilize multiview information, resulting in limited performance when capturing complex structures.
View Article and Find Full Text PDFBackground: The significance of the systemic inflammation response index (SIRI) in predicting the prognosis of patients with pancreatic cancer (PC) has been extensively explored; however, findings remain controversial. As such, this meta-analysis was performed to more precisely determine the utility of the SIRI in predicting PC prognosis.
Methods: A comprehensive literature search of the PubMed, Web of Science, Embase, and Cochrane Library databases for relevant studies, published up to June 25, 2024, was performed.