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- Explainable Deep Learning for Personalized Age Prediction With ...🔍
- PERSONALIZED EXPLANATION FOR MACHINE LEARNING🔍
- A novel explainable machine learning|based healthy ageing scale🔍
- Towards Explainable Machine Learning for Prediction of Disease ...🔍
- Isabelle Ader on LinkedIn🔍
- Improving fairness in personalized AI models🔍
Explainable machine learning framework to predict personalized ...
Explainable machine learning framework to predict personalized ...
Attaining personalized healthy aging requires accurate monitoring of physiological changes and identifying subclinical markers that predict ...
Explainable machine learning framework to predict personalized ...
Explainable machine learning framework to predict personalized physiological aging. David Bernard (1, 2) , Emmanuel Doumard (1) , Isabelle Ader (1) ...
Explainable machine learning framework to predict personalized ...
Explainable machine learning framework to predict personalized physiological aging. Aging Cell, 2023,. 22 (8), pp.e13872. 10.1111/acel.13872 ...
Explainable machine learning framework to predict personalized ...
... Home · Search; Explainable machine learning framework to predict personalized physiological aging. Explainable machine learning framework to predict ...
Explainable machine learning framework for predicting long-term ...
This research is the first to develop an explainable machine learning (ML)-based framework for long-term CVD risk prediction (low vs. high) among adolescents.
Explainable Deep Learning for Personalized Age Prediction With ...
Explainable Artificial Intelligence (XAI) methods have been recently introduced to provide interpretable decisions of ML and DL algorithms both at local and ...
Explainable machine learning framework to predict personalized ...
Explainable machine learning framework to predict personalized physiological aging. Aging Cell Pub Date : 2023-06-10. DOI : 10.1111/acel.13872.
PERSONALIZED EXPLANATION FOR MACHINE LEARNING - arXiv
Keywords: Explainable artificial intelligence, Interpretable machine learning, Personalization,. Customization, Interactive machine learning. Page 2. Schneider ...
A novel explainable machine learning-based healthy ageing scale
Machine learning can be utilized for that purpose, however, user reservations towards “black-box” predictions call for increased transparency ...
Towards Explainable Machine Learning for Prediction of Disease ...
Based on this state-of-the-art, we design and develop a pipeline consisting of data preparation, prediction, and explanation. Predictions are ...
Isabelle Ader on LinkedIn: Explainable machine learning framework ...
Isabelle Ader's Post · Explainable machine learning framework to predict personalized physiological aging · More Relevant Posts · Saudi Arabia ...
Improving fairness in personalized AI models
Artificial intelligence and machine learning are revolutionizing how we make decisions, with models being developed to provide personalized ...
A systematic review of Explainable Artificial Intelligence models and ...
Machine learning and deep learning are Artificial intelligence technologies that use algorithms to predict outcomes more accurately without relying on human ...
A Distinctive Explainable Machine Learning Framework for ... - MDPI
We used an Open-source dataset of 541 patients from Kerala, India. Among all the classifiers, the final multi-stack of ML models performed best ...
Explainable machine learning framework to predict the risk of work ...
Explainable machine learning framework to predict the risk of work-related neck and shoulder musculoskeletal disorders among healthcare ...
An Explainable AI Framework for Artificial Intelligence of Medical ...
Therefore, in this work, we leverage a custom XAI framework, incorporating techniques such as Local Interpretable Model-Agnostic Explanations ( ...
Explainable artificial intelligence model to predict acute critical ...
Here, we present an explainable AI early warning score (xAI-EWS) system for early detection of acute critical illness.
A review of Explainable Artificial Intelligence in healthcare
ELI5 library developed by MIT is a Python library for visualizing and debugging ML models. ELI5 supports various ML frameworks such as Scikit-learn, Keras, ...
Overview of explainable machine learning framework for CVD risk ...
... Local interpretability approaches such as LIME (Local Interpretable Model-Agnostic Explanations) and Shapley values [20][21][22] can explain the predictions ...
Explainable machine learning prediction of synergistic drug ...
2023. TLDR. A deep learning framework, Personalized Deep Synergy Predictor (PDSP), that enables the patient-specific single drug response data for customizing ...