Results 181 to 190 of about 10,090 (236)
Machine-Learning-Guided Design of Incommensurate Antiferroelectrics via Field-Driven Phase Engineering. [PDF]
Xu K +9 more
europepmc +1 more source
In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Advances in DCE-MRI Radiomics for Non-Invasive Prediction of Breast Cancer Molecular Subtypes: Research Progress and Clinical Translation. [PDF]
Yu Z +6 more
europepmc +1 more source
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti +4 more
wiley +1 more source
MetaComb: a meta-learning framework for drug combination response prediction from cell lines to patients. [PDF]
Guo C +8 more
europepmc +1 more source
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley +1 more source
Digital Twin Applications in Diabetes Management: Scoping Review. [PDF]
Sarani Rad F +4 more
europepmc +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source

