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Erratum: Spinal Muscular Atrophy Update in Best Practices: Recommendations for Diagnosis Considerations.
Neurol Clin Pract
February 2025
[This corrects the article DOI: 10.1212/CPJ.0000000000200310.
View Article and Find Full Text PDFThe Diagnostic Challenge of Sialolithiasis.
J Microsc Ultrastruct
February 2023
Department of Oral Biology, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia.
The major salivary glands (parotid, submandibular, and sublingual) are most frequently obstructed by calculi within the salivary gland, or more uncommonly, by ranulas. Despite the well-defined clinical and radiographic diagnostic features, sialolithiasis may sometimes be confused with sialadenitis and ranulas, especially when encountered in general dental practice. We, therefore, present a case that illustrates this diagnostic dilemma to highlight the salient features of all three conditions.
View Article and Find Full Text PDFLongitudinal Assessment of Structural and Functional Changes in Rod-cone Dystrophy: A 10-year Follow-up Study.
Ophthalmol Sci
November 2024
Faculty of Medicine, Dentistry and Health Sciences, Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Australia.
Purpose: Emerging clinical trials for inherited retinal disease (IRD) require an understanding of long-term progression. This longitudinal study investigated the genetic diagnosis and change in retinal structure and function over 10 years in rod-cone dystrophies (RCDs).
Design: Longitudinal observational follow-up study.
Automated Detection of Filamentous Fungal Keratitis on Whole Slide Images of Potassium Hydroxide Smears with Multiple Instance Learning.
Ophthalmol Sci
November 2024
Casey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Purpose: The diagnosis of fungal keratitis using potassium hydroxide (KOH) smears of corneal scrapings enables initiation of the correct antimicrobial therapy at the point-of-care but requires time-consuming manual examination and expertise. This study evaluates the efficacy of a deep learning framework, dual stream multiple instance learning (DSMIL), in automating the analysis of whole slide imaging (WSI) of KOH smears for rapid and accurate detection of fungal infections.
Design: Retrospective observational study.
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