Artificial intelligence (AI) and machine learning (ML) are revolutionizing the way we understand and predict soil processes. Yet, while data-driven models ...
BackgroundDementia remains a major clinical and public health challenge, and the window for effective intervention depends ...
Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...
Abstract: With the global energy makeup increasingly dominated by renewables, the demand for reliable and efficient forecasting tools in solar power generation has never been higher. In this paper, we ...
Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.
Abstract: Autism Spectrum Disorder (ASD) is a genetic and neurological condition that leads to difficulties in communication and social interaction. The global concern associated with ASD diagnosis is ...
🧬 Extract SAE features from protein language models (PLMs) 📊 Analyze and interpret learned features through association with protein annotations 🎨 Visualize feature patterns and relationships 🤗 ...
A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...
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