This dataset was produced by simulations done in "A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions"

DataCite Commons2024-07-02 更新60

All Species N Critical Loads

氮临界负荷

物种敏感性评估

These data include spatially varying N critical loads, by species, for all evaluated species in Coughlin et al. (2023).

Figshare2023-04-25 更新30

Data Sheet 1_Development and validation of an interpretable machine learning model for acute radiation dermatitis in breast cancer.pdf

乳腺癌放疗并发症预测

可解释性机器学习

Background and PurposeRadiation dermatitis (RD), a common adverse reaction in breast cancer radiotherapy, impairs quality of life and increases healthcare burdens. Developing an effective risk predict

NIAID Data Ecosystem20

Additional file 10 of Development and internal validation of an interpretable machine learning model to predict coagulopathy following extracorporeal membrane oxygenation: a retrospective multicenter study

ECMO后凝血病预测

可解释性机器学习

Supplementary Material 10.

NIAID Data Ecosystem50

Average of external scores (1, 2 & 3).

信用评分卡模型

可解释性机器学习

Credit scorecards are essential tools for banks to assess the creditworthiness of loan applicants. While advanced machine learning models like XGBoost and random forest often outperform traditional lo

NIAID Data Ecosystem30

Raw tree-level and SHAP metadata

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