This article presents a machine learning-based predictive framework for assessing organizational Decision-Making Quality (DMQ) using Big Data Analytics Capabilities (BDAC) in healthcare organizations. The proposed framework integrates five BDAC dimensions—organizational, technical, analytical, cognitive, and social—and evaluates four supervised machine learning classifiers: Artificial Neural Network (ANN), Naive Bayes (NB), Decision Tree (DT), and Support Vector Machine (SVM). The study is based on data collected from 205 healthcare professionals in Jordan. The experimental results demonstrate that the Naive Bayes classifier achieved the highest predictive accuracy (87%), highlighting the effectiveness of integrated BDAC dimensions in improving organizational decision-making.
This archive contains the data associated with PETIMOT: A Novel Framework for Inferring Protein Motions from Sparse Data Using SE(3)-Equivariant Graph Neural Networks. Lombard <i>et al.</i> 2026.For questions, please contact elodie.laine@sorbonne-universite.fr.
<i>Deep learning (DL) methods show promising potential for single-cell data analysis, yet required tremendous efforts in building the models. </i><i>To streamline the application of sequence-based DL methods in single-cell genomics, we established a two-layer CNN model as a basel…
AntiPatternLoggingMLA toolkit to collect, extract, and analyze logging usage and logging-related code snippets from GitHub repositories — focused on finding logging anti-patterns in machine learning code.The repository provides a CLI (implemented in <code>main.py</code>) with com…
<b>Title:</b> Precise Prediction on the Corrosion Prevention Ability of 1,2,4-Triazole Derivatives: An Artificial Neural Network Approach<br><b>Overview:</b><br>This record contains the computational dataset, quantitative structure-activity relationship (QSAR) parameters, and art…
The early identification of early allograft dysfunction (EAD) and the long-term prediction of graft-related adverse event-free survival (GRAEFS) are crucial for effective post-transplant management. The study encompassed two complementary analyses: (1) an early hemodynamic assess…