- Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning (Diabetes Metab J 2024;48:771-9)
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Yun C, Tang F, Lou Q
- KMID: 2559011
- Diabetes Metab J.
- 2024 Sep;48(5):1008-1011.
- doi: 10.4093/dmj.2024.0490
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- Objective Quantitation of EGFR Protein Levels using Quantitative Dot Blot Method for the Prognosis of Gastric Cancer Patients
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Xin L, Tang F, Song B, Yang M, Zhang J
- KMID: 2526332
- J Gastric Cancer.
- 2021 Dec;21(4):335-351.
- doi: 10.5230/jgc.2021.21.e32
Purpose: An underlying factor for the failure of several clinical trials of anti-epidermal growth factor receptor (EGFR) therapies is the lack of an effective method to identify patients who overexpress... -
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- Determining the Clinical Characteristics, Treatment Strategies, and Prognostic Factors for Mycoplasma pneumoniae Encephalitis in Children: A Multicenter Study in China
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Fan G, Guo Y, Tang F, Chen M, Liao S, Wang J
- KMID: 2543630
- J Clin Neurol.
- 2023 Jul;19(4):402-409.
- doi: 10.3988/jcn.2022.0328
Background and Purpose Most of the knowledge of Mycoplasma pneumonia (M. pneumoniae) encephalitis (MPE) in children is based on case reports or small case series. This study aimed to describe... -
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- Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning
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Yun C, Tang F, Gao Z, Wang W, Bai F, Miller JD, Liu H, Lee Y, Lou Q
- KMID: 2558044
- Diabetes Metab J.
- 2024 Jul;48(4):771-779.
- doi: 10.4093/dmj.2023.0033
Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and... -
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