Article

Interpretable machine learning model for data driven classification of Oral Health Related Quality of Life in Patients with Type 2 Diabetes Mellitus

2024-05-04

Abstract excerpt

Type 2 Diabetes Mellitus(T2DM) is a debilitating condition with a number of complications including those of the oral cavity which can further deteriorate patient’s general and oral health related quality of life (OHRQoL). Machine Learning (ML) can help assign an individual’s propensity to develop poor OHRQoL, given a set of variables, and at the same time identify the most important features contributing to this...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6f596d65-3f73-539e-96c8-63aa696e0103
DOI: 10.1101/2024.05.03.24306811

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Interpretable machine learning model for data driven classification of Oral Health Related Quality of Life in Patients with Type 2 Diabetes MellitusDOI 10.1101/2024.05.03.24306811Read

Comparative Performance of Linear Regression and Machine Learning Models for Predicting Glycemic Status in Uncontrolled Type 2 Diabetes: SHAP-Based AnalysisSemantic proximity Read

Multi-Dataset Diabetes Prediction Using Stacking Ensemble Learning and Explainable Artificial IntelligenceSemantic proximity Read

DiaHealth: Early Prediction of Type-2 Diabetes with Associated Risk Factors Using Machine Learning and Explainable AISemantic proximity Read

Identification and Validation of a Machine Learning Predictive Model for Type 2 Diabetes Mellitus Based on Inflammation-Related Indicators.Semantic proximity Read

Development of Explainable Machine Learning Framework for Early Detection and Risk Stratification of Diabetes in Age Specific VariationsSemantic proximity Read

Tongue Manifestations Predict Diabetic Macrovascular Disease in Type 2 Diabetes: A Machine Learning Model with SHAP InterpretationSemantic proximity Read

An Interpretable Machine Learning Model for the Diagnosis of Coronary Heart Disease in Patients with Type 2 Diabetes Mellitus: A Multi-Center Cohort StudySemantic proximity Read

A Data Analysis on Diabetic Patients Using Data Mining Tools and Prediction AlgorithmsSemantic proximity Read

Diabetes Risk Stratification Using Self‐Reported Health IndicatorsSemantic proximity Read

Predicting Dairy Milk Intake Recommendations Using Machine Learning Models: A Comparative AnalysisSemantic proximity Read

Risk Stratification for In-Hospital Mortality in Alzheimer’s Disease Using Interpretable Regression and Explainable AISemantic proximity Read