Results 161 to 170 of about 184,822 (218)
Comparative evaluation of machine learning and deep learning approaches for compressive strength prediction of geopolymer concrete. [PDF]
Ezz H, Bakr SM.
europepmc +1 more source
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
Atrial fibrillation prediction in patients with hypertrophic cardiomyopathy based on long-term follow-up data and machine learning model. [PDF]
Ding WX +7 more
europepmc +1 more source
A biotin‐modified artificial insertion peptide functionalized three‐dimensional high‐curvature‐TiO2 nano‐interface was engineered in a microfluidic chip to improve the isolation efficiency of small extracellular vesicles (sEVs). This chip balanced affinity, releasability, and extendibility, enabling high‐throughput recovery of sEVs for downstream ...
Le Wang +7 more
wiley +1 more source
Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review. [PDF]
Ku J, Singhal M, Burnette M, Hegazy SA.
europepmc +1 more source
This work proposed a pollen‐enhanced bionic mechanoreceptor based on ionic convection. Leveraging the ion anchoring effect of the pollen particle, the output performance could be ∼12 times higher than the original state. By employing deep learning models as AI brains, the feasibility of a sensory‐augmented prosthesis consisting of a pollen‐enhanced ...
Zi Hao Guo +7 more
wiley +1 more source
High-throughput analysis of multimodal monitoring data: the role of machine learning in early warning systems for high-risk neonates. [PDF]
Huo H +5 more
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source

