Mammal Community Responses to Increasing Puma Activity in a Suburban Preserve. [PDF]
Sonawane C +7 more
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Machine Learning Models for Objective Assessment of Vascular Anastomoses Using Computational Fluid Dynamics for Surgical Skill Training-A Retrospective Study. [PDF]
Kiss-Pápai L +5 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Enhancing accuracy in modelling highly multicollinear data using alternative shrinkage parameters for ridge regression methods. [PDF]
Akhtar N, Alharthi MF.
europepmc +1 more source
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula +10 more
wiley +1 more source
Integrating preliminary test and Stein-type techniques to improve estimation in the time-dependent Cox model. [PDF]
Ramezani R, Rabiei MR, Arashi M.
europepmc +1 more source
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
New robust two-parameter estimator for overcoming outliers and multicollinearity in Poisson regression model. [PDF]
Mohammad HH +6 more
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source

