Results 71 to 80 of about 1,474 (168)

Self-Information-Driven Gated Graph Convolutional Network for Occluded Person Re-Identification. [PDF]

Sensors (Basel)
Guo W, Meng J, Xue Y, Fan Y, Fang Z.
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

From data to discovery: The rise of information-theoretic predictive models in drug development. [PDF]

Sci Rep
Saied H, Alfahad O, Aljaffer AA, AlOmari AK, Saleh MA, Malaekah E.   +5 more
europepmc   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
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, Nicholas Ballard   +1 more
wiley   +1 more source

Quantifying coupling and causality in dynamic bivariate systems: a unified framework for time-domain, spectral, and information-theoretic analysis. [PDF]

Front Netw Physiol
Sparacino L, Pinto H, Barà C, Antonacci Y, Pernice R, Rocha AP, Faes L.   +6 more
europepmc   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

ERG-Graph: Graph Signal Processing of the Electroretinogram for Classification of Neurodevelopmental Disorders. [PDF]

Bioengineering (Basel)
Mercado-Diaz LR, Pinzon-Arenas JO, Constable PA, Lee IO, Loh L, Thompson DA, Posada-Quintero HF.   +6 more
europepmc   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source

Information theoretic measures of neural and behavioural coupling predict representational drift. [PDF]

PLoS Comput Biol
Heiney K, Józsa M, Rule ME, Sprekeler H, Nichele S, O'Leary T.   +5 more
europepmc   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source