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Birth and weaning weights in buffalo calves resulting from artificial insemination or natural mating in Venezuela
Published 2023-11-01“…During the study period, 15 AI and ten natural mating bulls were used. Data were analyzed by the general linear model of SAS. …”
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Power-free plasma separation based on negative magnetophoresis for rapid biochemical analysis
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Development of the inner ear and regeneration of hair cells after hearing impairment
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Segmentation of Laser Marks of Diabetic Retinopathy in the Fundus Photographs Using Lightweight U-Net
Published 2021-01-01“…With accurate segmentation and high numeric metrics, the lightweight U-Net method showed its reliable performance in automatically segmenting laser marks in fundus photographs, which could help the AI assist the diagnosis of DR in the severe stage.…”
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Interpreting machine learning models based on SHAP values in predicting suspended sediment concentration
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Occurrence, risks, and mitigation of antibiotic pollution in Bangladeshi aquaculture systems
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Affective valence predictors from real-world based short sprint interval training
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Ocular changes after simultaneous kidney-pancreas transplant
Published 2022-05-01“…Sklifosovskiy Research Institute for Emergency Medical Aid, Moscow, Russian Federation</b> </p> <p> <b><sup>3</sup>A.I. Yevdokimov Moscow University of Medicine & Dentistry, Moscow, Russian Federation</b> </p> <p> <b><sup>4</sup>Research Institute of Public Health Organization and Medical Management, Moscow, </b> <b>Russian Federation</b> </p> <p> <i>Type 1 diabetes (T1D) is one of the most common chronic diseases in young individuals. …”
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Protein identification using Cryo-EM and artificial intelligence guides improved sample purification
Published 2025-06-01“…It highlights the potential of combining Cryo-EM with AI-driven tools for accurate protein identification and addressing purification challenges across diverse contexts in protein science.…”
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Unlocking the Potential of Receptor-Based Approaches in Diabetes Treatment
Published 2025-01-01“…Additionally, patient monitoring, adherence, and self-management will be greatly aided by the integration of digital health technology, telemedicine, and artificial intelligence (AI), thus leading to better treatment outcomes and patient quality of life. …”
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