Results 211 to 220 of about 1,354,041 (282)
Hands-on cybersecurity training behavior data for process mining. [PDF]
Ošlejšek R +2 more
europepmc +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Optimizing emergency department efficiency: a comparative analysis of process mining and simulation models to mitigate overcrowding and waiting times. [PDF]
Davari F +3 more
europepmc +1 more source
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley +1 more source
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
What makes life for process mining analysts difficult? A reflection of challenges. [PDF]
Zimmermann L, Zerbato F, Weber B.
europepmc +1 more source
Automatic Determination of Quasicrystalline Patterns from Microscopy Images
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
Process mining to investigate the relationship between clinical antecedents and injury risk, severity and return to play in professional sports. [PDF]
Pi-Rusiñol R +3 more
europepmc +1 more source

