- Interpretable machine learning for dementia🔍
- Robust and interpretable AI|guided marker for early dementia ...🔍
- An explainable machine learning approach for Alzheimer's disease ...🔍
- An Interpretable Machine Learning Tool for In|Home Screening of ...🔍
- Prediction of conversion to dementia using interpretable machine ...🔍
- Predicting Alzheimer's Disease with Interpretable Machine Learning🔍
- A robust and interpretable machine learning approach using ...🔍
- An Interpretable Machine Learning Model with Deep ...🔍
Interpretable machine learning for dementia
Interpretable machine learning for dementia: A systematic review
Interpretability is key for the clinical application of machine learning in decision-making tools for dementia prediction. The need for model ...
Interpretable machine learning for dementia: A systematic review
Future work should incorporate clinicians to validate explanation methods and make conclusive inferences about dementia-related disease pathology.
Interpretable machine learning for dementia: A systematic review
Introduction Machine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited clinical impact.
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 ...
Machine learning (ML) models offer a promising tool for identifying individuals at risk of AD. However, current research tends to prioritize ML accuracy.
An Interpretable Machine Learning Tool for In-Home Screening of ...
An Interpretable Machine Learning Tool for In-Home Screening of Agitation Episodes in People Living with Dementia · Abstract · Full Text · Info/ ...
Prediction of conversion to dementia using interpretable machine ...
Therefore, this study aimed to improve the predictive power of aMCI patients' conversion to dementia by using an interpretable machine learning ...
Predicting Alzheimer's Disease with Interpretable Machine Learning
Interpretable machine learning showed promise in screening high-risk AD individual and could further identify key predictors for targeted ...
A robust and interpretable machine learning approach using ...
In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal lobe atrophy, tau ...
Predicting Alzheimer's Disease with Interpretable Machine Learning
In addition, taurine, inosine, xanthine, marital status, and L.Glutamine also showed importance to AD prediction. Conclusion: Interpretable ...
An Interpretable Machine Learning Model with Deep ... - SpringerLink
Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine ...
Interpretable Hierarchical Deep Learning Model for Noninvasive ...
They achieved a crossvalidation accuracy of 97% in distinguishing AD subjects from control subjects in the DementiaBank data set. Fritsch et al.
Identifying the presence and severity of dementia by applying ...
We formulate these two tasks as classification problems and address them using machine learning models based on random forests and decision tree ...
[2308.07778] An Interpretable Machine Learning Model with Deep ...
However, some machine learning methods based on imaging data have poor interpretability because it is usually unclear how they make their ...
Interpretable Machine Learning in Alzheimer's Disease Dementia
Browse items by: Publication Date, Author Title, Subject, Department, Help, Help, Sign on to: My MacSphere, Receive email updates, Edit Profile, Search ...
Interpretable machine learning for dementia: a systematic review
Abstract. Introduction: Machine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited clinical impact.
Interpreting artificial intelligence models: a systematic review on the ...
The Local Interpretable Model-agnostic Explanations (LIME) and Shaply Additive exPlanation (SHAP) frameworks have grown as popular interpretive ...
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 ...
Automatic CDT Scoring Using Machine Learning with Interpretable ...
In this paper, we propose a novel automatic CDT scoring method based on interpretable features using machine learning.
Development and validation of an interpretable deep learning ...
Our framework linked a fully convolutional network, which constructs high resolution maps of disease probability from local brain structure to a ...