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September 20, 2024BMC Endocrine DisordersOpen Access

Establishment and external validation of an early warning model of diabetic peripheral neuropathy based on random forest and logistic regression

Lujie Wang Jiajie Li Yixuan Lin Huilun Yuan Zhaohui Fang Aihua Fei Guo-Ming Shen Aijuan Jiang

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Abstract

The primary objective of this study was to investigate the risk factors for diabetic peripheral neuropathy (DPN) and to establish an early diagnostic prediction model for its onset, based on clinical data and biochemical indices.

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Cite This Study

Wang et al. (2024) studied this question.

synapsesocial.com/papers/68e57d34b6db64358751c298 https://doi.org/10.1186/s12902-024-01728-9

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Construction of an Early Risk Prediction Model for Type 2 Diabetic Peripheral Neuropathy Based on Random Forest2024 · 6 citations
2Development and validation of a risk prediction model for painful diabetic peripheral neuropathy in type 2 diabetes mellitus: a multicenter retrospective study2025 · 2 citations
3Exploration of a Multimodal Machine Learning Model Integrating Ultrasound and Clinical Indicators for the Diagnosis of Diabetic Peripheral NeuropathyOriginal Research · 2026 · 3 citations
4Construction of a Nomogram Prediction Model for the Risk of Type 2 Diabetic Peripheral Neuropathy2024
5Development and validation of a risk nomogram model for predicting peripheral neuropathy in patients with type 2 diabetes mellitus2024 · 3 citations

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Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors2024
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Application of construction and validation of logistic regression model in risk prediction of non‐proliferative diabetic retinopathy in type 2 diabetes mellitus2026

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