Results 161 to 170 of about 40,557 (254)

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Genetic architecture of backfat thickness in laying hens: implications for extended egg production. [PDF]

Genet Sel Evol
Bédère N, Hérault F, Bécot L, Burlot T, Diot C, Lagarrigue S, Le Roy P.   +6 more
europepmc   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Cultural Biases and Clinical Variation. [PDF]

Clin Pract
Gasulla Ó, Sarría-Santamera A, Mazaira-Font FA, García-Montero C, Fraile-Martinez O, Cantalapiedra D, Carrillo-Rodríguez MF, Gómez-Valcárcel B, Ortega MÁ, Álvarez-Mon M, Asúnsolo A.   +10 more
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Brain MRI Radiomic First-Order Features for Presurgical Prediction of Meningioma Grading. [PDF]

J Neuroimaging
Pineda-Ibarra C, Puig J, Nuñez-Leiva D, Rodríguez Y, Mora J, Medrano-Martorell S, Pariente JC, Comas-Cufí M, Niñerola-Baizán A, Farré-Melero A, Reyes-Barrios DA, Aldecoa I, Oleaga L, González-Ortiz S.   +13 more
europepmc   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Correction to "Genomic, Phenotypic, and Environmental Correlates of Speciation in the Midwife Toads (Alytes)". [PDF]

Mol Ecol
europepmc   +1 more source

Risk factors, pathologies and control of gut-dwelling roundworms in chickens. [PDF]

Helminthologia
Khan N, Khan W, Shoaib M, Althubyani SA, Yousaf M.   +4 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source