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Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten
In education data mining (EDM) communities, machine learning has achieved remarkable success in discovering patterns and structures to tackle educational challenges.
Towards Modeling Uncertainties of Self-explaining Neural Networks via Conformal Prediction
To tackle the aforementioned challenges, in this paper, we design a novel uncertainty modeling framework for self-explaining networks, which not only demonstrates strong distribution-free uncertainty modeling performance for the generated explanations in the interpretation layer but also excels in producing efficient and effective prediction sets for the final predictions based on the informative high-level basis explanations.
m6 A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD
This risk model based on the m6 A-based lncRNAs may be promising for the clinical prediction of prognoses and immunotherapeutic responses in LUAD patients.
