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Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model
Published 2014-01-01“…A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.…”
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462
Publisher Correction: A metagenomic catalogue of the ruminant gut archaeome
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Risk factors for fear of falling in stroke patients: a systematic review and meta-analysis
Published 2022-06-01Get full text
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The Effects of Sandstorms on the Climate of Northwestern China
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Genome-wide association study on color-image-based convolutional neural networks
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The Existence of Weak D-Pullback Exponential Attractor for Nonautonomous Dynamical System
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Antibiotic Prophylaxis in Transarterial Therapy of Hepatocellular Carcinoma: A Meta-Analysis
Published 2012-01-01Get full text
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A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction
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Synchronization of Neuronal Circuits with Ring Connection on PSpice
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Threshold dynamics of a time periodic and two–group epidemic model with distributed delay
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Periodic Motion and Transition of a Vibro‐Impact System with Multilevel Elastic Constraints
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