Results 131 to 140 of about 3,522,020 (238)

AID-RT: Standardising Artificial Intelligence Documentation in RadioTherapy with a domain-specific model card. [PDF]

Phys Imaging Radiat Oncol
Barragán-Montero AM, Huet-Dastarac M, Herranz-Hernández SM, Tengler B, Buhl ES, Galapon A, Cárdenas CE, Fusella M, Herbin G, de Hond Y, Knuth F, Malone C, van Ooijen P, Robert C, Zeverino M, Hurkmans C, Janssen T, Korreman SS, Brouwer CL.   +18 more
europepmc   +1 more source

Lumped modeling of bubbling fluidized beds for high‐temperature processes

AIChE Journal, EarlyView.
Abstract Bubbling fluidized beds (BFBs) have been a source of study for multiple decades. Among other applications, they can be used as scalable reactors for the conversion of biomass and waste resources to fuels. Several experimental and computational studies have been devoted to correlating the interplay of hydrodynamics and heat and mass transfer in
Ravi Ramesh, Elyas Moghaddam, Wiebren de Jong, Johan T. Padding   +3 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

The Human Mind in Dialogue With its Replica AI - a Historical Perspective. [PDF]

Integr Psychol Behav Sci
Klempe SH.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

A novel spatiotemporal decomposition and identification of sparse equations for human brain deformation. [PDF]

Sci Rep
Arani AHG, Alshareef AA, Pham DL, Okamoto RJ, Bayly PV.   +4 more
europepmc   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

The global structure of classroom social networks predicts academic and psychosocial adjustment. [PDF]

PNAS Nexus
Neuendorf C, Masuda N, Murayama K.
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source