AUTOMATED DETECTION, LOCALIZATION, AND SEVERITY ASSESSMENT OF PROXIMAL DENTAL CARIES FROM BITEWING RADIOGRAPHS USING DEEP LEARNING

Automated Detection, Localization, and Severity Assessment of Proximal Dental Caries from Bitewing Radiographs Using Deep Learning

Background/Objectives: Dental caries is a widespread chronic infection, affecting a large segment of the population.Proximal caries, in particular, present a distinct obstacle for early identification owing to their position, which hinders clinical inspection.Radiographic assessments, particularly bitewing images (BRs), are frequently utilized to d

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Rapid diagnosis of Talaromyces marneffei infection by metagenomic next-generation sequencing technology in a Chinese cohort of inborn errors of immunity

Talaromyces marneffei (T.marneffei) is an opportunistic pathogen.Patients with inborn errors of immunity (IEI) have been increasingly diagnosed with T.marneffei in recent years.The disseminated infection of T.marneffei can be life-threatening without liftmaster expansion board timely and effective antifungal therapy.Rapid and accurate pathogenic mi

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Exponentially Increasing Trend of Infected Patients with COVID-19 in Iran: A Comparison of Neural Network and ARIMA Forecasting Models

Background: The outbreak of COVID-19 is rapidly spreading around the world and became a pandemic disease.For help to better planning of interventions, this study was conducted to forecast the number of daily new infected cases with COVID-19 for next thirty days in Iran.Methods: The information of observed Iranian new cases from 19th Feb to 30th Mar

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