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A deep learning based model for diabetic retinopathy grading.

Sci Rep

January 2025

Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.

Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability and classification accuracy.

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Emergency care units in Hungary treat approximately 140-180 thousand head injuries of varying se'verity each year. These head injuries are mainly caused by traffic accidents, assaults, or domestic accidents. The outpatient care record contains details about the circumstances and underlying mechanisms of the head injury, the results of physical and imaging examinations, and therapeutic recommendations.

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Objective: This systematic review was conducted to synthesize current research on the role of repeated transurethral resection of the bladder (re-TURB) and the emerging use of magnetic resonance imaging (MRI) in discerning patient suitability for safely foregoing this procedure.

Evidence Acquisition: Employing a methodical literature search, we consulted several bibliographic databases including PubMed, Science Direct, Scopus, and Embase. The review process adhered strictly to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines.

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Background: Precision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. ​​​​In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.

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Morphological and molecular phylogeny of sp. (Digenea: Clinostomidae) metacercariae, using DNA barcode from a South American freshwater fish.

J Helminthol

January 2025

Universidade Federal de Alagoas (UFAL), Instituto de Ciências Biológicas e da Saúde, Departamento de Patologia e Parasitologia, Maceió, Alagoas, Brasil.

Here, we present a comprehensive morphological and molecular phylogenetic analysis of sp. (Digenea: Clinostomidae) metacercariae parasitizing two freshwater fish species from Southeast Brazil: (piranha) and (tambuatá). The morphological examination revealed distinct characteristics of metacercariae in each host.

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