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Prediction of conversion to dementia using interpretable machine ...


Prediction of conversion to dementia using interpretable machine ...

We were able to propose a predictive algorithm for each aMCI individual's conversion to dementia using the IML technique.

Prediction of conversion to dementia in subjects with amnestic mild ...

This study aims to improve the predictive power of aMCI patients' conversion to dementia by using an interpretable machine learning (IML) model ...

Prediction of conversion to dementia using interpretable machine ...

A predictive algorithm is proposed for each aMCI individual's conversion to dementia using an interpretable machine learning (IML) algorithm that can ...

Prediction of conversion to dementia using interpretable machine ...

Prediction Model of Conversion to Dementia Risk in Subjects with Amnestic Mild Cognitive Impairment:... ... Background: Patients with amnestic ...

Interpretable machine learning for dementia: A systematic review

For the more challenging task of identifying individuals with mild cognitive impairment (MCI) who later converted to Alzheimer's disease (pMCI) ...

Robust and interpretable AI-guided marker for early dementia ...

Our results provide evidence for a robust and explainable clinical AI-guided marker for early dementia prediction that is validated against ...

An explainable machine learning approach for Alzheimer's disease ...

The early diagnosis of Alzheimer's disease (AD) presents a significant challenge due to the subtle biomarker changes often overlooked.

Development and validation of an interpretable machine learning ...

A large number of studies have shown that the risk of conversion to dementia in MCI patients is much higher than that of the healthy elderly ...

Dementia prediction in the general population using clinically ...

External validation studies on prognostic models for dementia have highlighted the need for updated models. The use of machine learning in ...

Prediction of conversion to dementia using interpretable machine ...

Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment ... Authors: Min Young Chun; Chae ...

Machine Learning for Dementia Prediction: A Systematic Review ...

One of the disease detection problems that AI and ML researchers have focused on is dementia detection using ML methods. Numerous automated ...

Predicting the Conversion from Mild Cognitive Impairment to ... - MDPI

Through the analysis of longitudinal data, spanning from the baseline visit to the 12-month follow-up, a predictive model was constructed. The proposed model ...

Interpretable machine learning for dementia: A systematic review

Borchert and colleagues recently reviewed neuroimaging-based machine learn- ing for dementia prediction, with recommendations on how to increase ...

An interpretable multiparametric radiomics model of basal ganglia to ...

Two models were developed to predict dementia development: (1) a clinical model—age, disease duration, and cognitive composite scores, and (2) a ...

A hybrid machine learning approach for prediction of conversion ...

Novel prognostic machine learning approach accurately predicts dementia conversion. ... Features generated via unsupervised learning used as input ...

Interpreting artificial intelligence models: a systematic review on the ...

... Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment. Front Aging ...

Comparison of Machine Learning-based Approaches to Predict the ...

In Mild Cognitive Impairment (MCI), identifying a high risk of conversion to Alzheimer's Disease Dementia (AD) is a primary goal for patient ...

Improving Early Prognosis of Dementia Using Machine Learning ...

A recent study of machine learning models concluded that many challenges still exist for dementia risk prediction in terms of methodological ...

Explainable Machine Learning with Pairwise Interactions for ... - MDPI

This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different ...

Identifying the presence and severity of dementia by applying ...

Various graph-based or feature-dependent prediction and progression models have been proposed. Whenever these models exploit information in the ...