Urban air pollution remains a critical challenge for public health and environmental sustainability. This study investigates the predictive capabilities of five machine learning (ML) models: Linear Re

Figshare2025-11-07 更新50

DataSheet7_Solubilization of inclusion bodies: insights from explainable machine learning approaches.PDF

蛋白质纯化

可解释机器学习

We present explainable machine learning approaches for gaining deeper insights into the solubilization processes of inclusion bodies. The machine learning model with the highest prediction accuracy fo

NIAID Data Ecosystem20

Data and code for machine learning analysis of aeolian transport processes

风沙输运建模

可解释机器学习

This repository provides representative datasets and analysis codes supporting a study on the application of machine learning methods to aeolian transport processes. The dataset includes example and

NIAID Data Ecosystem20

Replication Code and Data for "Explainable Machine Learning Reveals Shifting Drivers of Mortuary Differentiation: A 1,500-Year Sequence from Liuwan, Northwest China"

墓葬考古分析

可解释机器学习

This repository contains the replication code and data for the analysis presented in the accompanying article. The dataset comprises 1,485 burials from the Liuwan Cemetery (柳湾墓地), Ledu District, Qing

Zenodo2026-04-06 更新30

Recommendations to avoid bias for explainable machine learning models that use audio recordings for screening in laryngology.

医疗AI筛查

可解释机器学习

Recommendations to avoid bias for explainable machine learning models that use audio recordings for screening in laryngology.

NIAID Data Ecosystem20