Study on the construction of risk prediction model and efficacy ...

Age, infrequent exercise, inadequate sleep and depression could be risk factors for cognitive decline in elderly individuals with type 2 diabetes, and the ...

Abstract. This study aims to construct a predictive model for assessing the risk of cognitive decline among elderly patients diagnosed with type 2 diabetes ...

Study on the construction of risk prediction model and efficacy ...

This study aims to construct a predictive model for assessing the risk of cognitive decline among elderly patients diagnosed with type 2 diabetes and...

Construction and verification of risk prediction model of osteoporotic ...

... model is effective. Conclusion. In this study, a OPF risk prediction model is established and its prediction efficiency is verified, which ...

Construction of a machine learning-based risk prediction model for ...

Finally, the prediction efficiency of the three models was compared. Results: In this study, 18 variables were included, and LASSO ...

Construction of a risk prediction model based on the analysis of MRI ...

This study is aimed at constructing a risk prediction model for patients with triple- ... (MRI) and verifying the efficacy of the model. 150 ...

Construction of Risk Prediction Models for Enterprise Finance ...

In summary, this study employs the K-means clustering algorithm to enhance the effectiveness of employee performance appraisal management, ...

Construction and validation of a clinical prediction model for sepsis ...

... predictive efficiency of PI through this series of studies ... In this study, for the in-hospital mortality risk prediction model ...

Construction of a risk prediction model for Alzheimer's disease in the ...

In this study, a simple nomogram was drawn to predict the risk of AD in the elderly population. Methods. Nine variables affecting the risk of AD ...

Construction and validation of a risk-prediction model for ...

This study aims to construct a novel risk-prediction model for AL following ... The effectiveness of the model's external validation was evaluated ...

Construction project risk prediction model based on EW-FAHP and ...

The risk weight is input into the 1D-CNN model for training and learning, and the prediction values of construction period risk and cost risk ...

Statistical Primer: developing and validating a risk prediction model

Risk prediction models are widely studied in the cardiothoracic surgical literature with most developed using logistic regression. For a risk ...

Construction and validation of risk prediction models for pulmonary ...

Conclusion: This study developed six ML models, with the RF model exhibiting the highest predictive efficacy and clinical benefit in the ...

Construction of a predictive model for osteoporosis risk in men

Compared with these more complex machine learning methods, although the prediction efficiency is slightly lower, our problem input is simpler, ...

Construction of risk prediction model for hypothermia during ...

Studies have shown that intraoperative hypothermia can lead to complications such as increased intraoperative blood loss, prolonged anaesthesia ...

Construction of a financial default risk prediction model based on the ...

The proposed LightGBM algorithm can effectually judge the default risk of users on P2P platforms compared to the traditional machine learning ...

Construction of Cybersecurity and Risk Prediction Model for...

Integrating with the Markov time-varying model enhances the efficiency over traditional Boltzmann machines, facilitating nuanced network state ...

Construction of Risk Prediction Model for Alzheimer's Disease ...

Therefore, this study intends to determine the independent risk factors affecting the condition of Alzheimer's disease patients by logistic regression combined ...

Evaluation of clinical prediction models (part 1): from development to ...

... effectiveness study) or requires updating (eg, recalibration). To ... Development and external validation of a risk prediction model ...

Building Risk Prediction Models for Type 2 Diabetes Using Machine ...

We built several machine learning models for predicting type 2 diabetes, including support vector machine, decision tree, logistic regression, random forest, ...