Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun +9 more
wiley +1 more source
Large language model ensemble for automated TNM staging from radiology reports. [PDF]
Yeh WC +4 more
europepmc +1 more source
Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford +3 more
wiley +1 more source
Explainable multimodal AI and neuro-symbolic clinical decision support system for chronic eye disease management: a digital health implementation study. [PDF]
Wang MH +16 more
europepmc +1 more source
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li +10 more
wiley +1 more source
Generative artificial intelligence in medical education: from knowledge assessment to clinical reasoning and professional competence. [PDF]
Xie R, Zhang B, Xiao L.
europepmc +1 more source
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park +3 more
wiley +1 more source
Intelligent automated essay scoring under uncertainty using type 2 neutrosophic ontologies. [PDF]
Darwish SM, Bagi NA, El-Shoafy NA.
europepmc +1 more source
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source
A Phosphorylation‐Induced Micellization Switch in the Low‐Complexity Domain of TDP‐43
Phosphorylation of TAR DNA‐binding protein's 43 kDa (TDP‐43) low‐complexity domain by casein kinase 1 delta (CK1δ) acts as a molecular switch, redirecting its self‐assembly from macroscopic phase separation toward finite‐sized, spherical block‐copolymer micelles of ∼30 nm.
Rodrigo F. Dillenburg +16 more
wiley +1 more source

