Results 231 to 240 of about 9,518 (289)

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Type I interferon drives T cell responses to amyloid beta in the central nervous system. [PDF]

Nat Commun
Michel JJ, Sanghvi K, Rosenbauer J, Humbs L, Dierssen CT, Grudzenski-Theis S, Sachs V, Jähne K, Degenhardt K, Frölich L, Herms J, Fatar M, Platten M, Bunse L.   +13 more
europepmc   +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

AI-augmented reliability in CI/CD: a framework for predictive, adaptive, and self-correcting pipelines. [PDF]

Front Artif Intell
Dhawan R, Dhawan M.
europepmc   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Dual-trigger model of CD20 escape: NONO regulation and cryptic splicing induced by transcript overload in pediatric B-ALL. [PDF]

Front Immunol
Kermani M, Maxeiner S, Alt F, Ziegler N, König J, Paret C, Faber J.   +6 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

From pixels to planning: scale-free active inference. [PDF]

Front Netw Physiol
Friston K, Heins C, Verbelen T, Da Costa L, Salvatori T, Markovic D, Tschantz A, Koudahl M, Buckley C, Parr T.   +9 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
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, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Fast Spiking Interneurons Autonomously Generate Fast Gamma Oscillations in the Medial Entorhinal Cortex with Excitation Strength Tuning ING-PING Transitions. [PDF]

eNeuro
Williams B, Vedururu Srinivas A, Baravalle R, Fernandez FR, Canavier CC, White JA.   +5 more
europepmc   +1 more source