Tech Xplore

Easier parameter tuning for prediction using echo state networks

Neural networks, a fascinating technology inspired by the human brain, form the basis of artificial intelligence. These ...
Scientific Research Publishing

Improving Demand Forecasting for Haemodialysis Consumables in Zambia: A Comparative Analysis of Time-Series Models ()

In many public healthcare systems, particularly in resource-constrained environments, time-series forecasting models offer a practical, interpretable, and evidence-based alternative (Stacey et al., ...
Tech Xplore

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...
IEEE

Tennis match outcome prediction using machine learning and in-match statistics

Abstract: Machine learning has become a cornerstone of sports analytics, including tennis, which is an ideal arena for its application due to the abundance of comprehensive tennis data. This study ...

Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
IEEE

Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Objective: This study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney ...