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Improved Glycemic Control in Insulin-Treated Individuals With Poorly Controlled Type 2 Diabetes Through Combined Structured Education With Real-Time Continuous Glucose Monitoring.
J Diabetes Sci Technol
January 2025
Division of Endocrinology and Metabolism, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Background: We evaluated the efficacy of structured individualized education combined with real-time continuous glucose monitoring (rt-CGM, Dexcom G6) in improving glycemic outcomes in insulin-treated adults with poorly controlled type 2 diabetes (T2D).
Methods: This multicenter, 16-week, single-arm study included 66 adults with T2D (multiple daily insulin [MDI]: 33; basal insulin: 33) with a ≥7.8%.
Context: Anemia is a medical condition resulting from a reduction in the number of red blood cells below the reference range. It is a major public health problem, particularly among adolescents, as it can have negative effects on cognitive performance, growth and reproduction. This study aims to assess the determinants of anemia among adolescents in schools in the city of Douala.
View Article and Find Full Text PDFHigh-resolution cryo-EM using a common LaB 120-keV electron microscope equipped with a sub-200-keV direct electron detector.
Sci Adv
January 2025
Ramaciotti Centre for Cryo-Electron Microscopy, Monash University, Clayton, VIC, Australia.
High-resolution cryo-electron microscopy (cryo-EM) requires costly 200- to 300-keV cryo-transmission electron microscopes (cryo-TEMs) with field emission gun (FEG) sources, stable columns, constant-powered lenses, autoloader, and direct electron detectors (DED). Recent advances in 100-keV imaging with the emergence of sub-200-keV optimized DED technology promises the development of more affordable cryo-TEMs. So far, 100-keV imaging has required microscopes with FEG sources.
View Article and Find Full Text PDFConstruction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features.
Int J Gen Med
December 2024
Department of Cardiology, Shaanxi Provincial People's Hospital, Xi'an, People's Republic of China.
Purpose: Heart failure (HF) is a clinical syndrome in which structural or functional abnormalities of the heart result in impaired ventricular filling or ejection capacity. In order to improve the adaptability of models to different patient populations and data situations. This study aims to develop predictive models for HF risk using six machine learning algorithms, providing valuable insights into the early assessment and recognition of HF by clinical features.
View Article and Find Full Text PDFEvaluation of Band Selection for Spectrum-Aided Visual Enhancer (SAVE) for Esophageal Cancer Detection.
J Cancer
January 2025
Department of Mechanical Engineering, National Chung Cheng University, Chia-Yi 62102, Taiwan.
Band selection is a common approach to reduce the data dimensionality of hyperspectral imagery. It extracts several bands of importance in some sense by taking advantage of high spectral correlation. In medical imaging, narrow-band imaging (NBI) is an imaging technique for endoscopic diagnostic medical tests, where light of specific blue and green wavelengths is used to enhance the detail of certain aspects of the surface of the mucosa.
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