Risk-Profile and Feature Selection Comparison in Diabetic Retinopathy

One of the main microvascular complications presented in the Mexican population is diabetic retinopathy which affects 27.50% of individuals with type 2 diabetes. Therefore, the purpose of this study is to construct a predictive model to find out the risk factors of this complication. The dataset con...

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Veröffentlicht in:	Journal of personalized medicine 2021-12, Vol.11 (12), p.1327
Hauptverfasser:	Maeda-Gutiérrez, Valeria, Galván-Tejada, Carlos E, Cruz, Miguel, Galván-Tejada, Jorge I, Gamboa-Rosales, Hamurabi, García-Hernández, Alejandra, Luna-García, Huizilopoztli, Gonzalez-Curiel, Irma, Martínez-Acuña, Mónica
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Cholesterol Creatinine Datasets Decision trees Diabetes Diabetes mellitus (non-insulin dependent) Diabetic retinopathy Diagnosis Feature selection Glomerular filtration rate High density lipoprotein Laboratories Learning algorithms Machine learning Microvasculature Neural networks Patients Performance evaluation Precision medicine Prediction models Retinopathy Risk factors Sensitivity analysis Statistical analysis Support vector machines Values
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