Background: The application of deep learning (DL) to diagnostic dermatology has been the subject of numerous studies, with some reporting skin lesion classification performance on curated datasets comparable to that of experienced dermatologists. Most skin disease images encountered in clinical settings are macroscopic, without dermoscopic information, and exhibit considerable variability. Further research is necessary to determine the generalizability of DL algorithms across populations and acquisition settings.
View Article and Find Full Text PDFYbCoSb, being a well-studied system, has shown notably high thermoelectric performance due to the Yb filler atom-driven large concentration of charge carriers and lower value of thermal conductivity. In this work, the thermoelectric performance of YbCoTiSb (where = 0, = 0 and = 0.4, = 0, 0.
View Article and Find Full Text PDFBackground: The aim of this study is to determine the current practice level of family planning and the associated factors among public secondary school teachers in Enugu East Senatorial District.
Method: A cross-sectional study was carried out among public secondary school teachers, aged 18 - 60 years, in Enugu East Senatorial District, using probability proportional to size sampling and systematic random sampling to select 1000 participants. Binary and multiple logistic regression analyses were used to determine association.
Phakomatosis pigmentovascularis is a diagnosis that denotes the coexistence of pigmentary and vascular birthmarks of specific types, accompanied by variable multisystem involvement, including CNS disease, asymmetrical growth, and a predisposition to malignancy. Using a tight phenotypic group and high-depth next-generation sequencing of affected tissues, we discover here clonal mosaic variants in gene PTPN11 encoding SHP2 phosphatase as a cause of phakomatosis pigmentovascularis type III or spilorosea. Within an individual, the same variant is found in distinct pigmentary and vascular birthmarks and is undetectable in blood.
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