Results 91 to 100 of about 13,427 (268)

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

Natural language processing to identify lupus nephritis phenotype in electronic health records

BMC Medical Informatics and Decision Making
Background Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and
Yu Deng, Jennifer A. Pacheco, Anika Ghosh, Anh Chung, Chengsheng Mao, Joshua C. Smith, Juan Zhao, Wei-Qi Wei, April Barnado, Chad Dorn, Chunhua Weng, Cong Liu, Adam Cordon, Jingzhi Yu, Yacob Tedla, Abel Kho, Rosalind Ramsey-Goldman, Theresa Walunas, Yuan Luo   +18 more
doaj   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

PMkbase (version 1.0): an interactive web-based tool for tracking bacterial metabolic traits using phenotype microarrays made interoperable with sequence information and visualizing/processing PM data

Microbiology Spectrum
Bacteria showcase remarkable metabolic diversity and traits, even among strains of the same species. In recent years, a large number of bacterial genomes have been sequenced, leading to the elucidation and documentation of genomic differences and ...
K. Jayanth Krishnan, Ying Hefner, Richard Szubin, Jonathan Monk, David T. Pride, Bernhard Palsson   +5 more
doaj   +1 more source

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

3D modeling and volume measurement of bulk grains stored in large warehouses using bi-temporal multi-site terrestrial laser scanning data

Journal of Agricultural Engineering
Terrestrial laser scanning (TLS) is a promising technology for quantity checking huge grain stocks with low cost, light workload and high efficiency. Existing applications of TLS in bulk grain measurement and quantification lack the ability to capture complete structural information of grain bulks and thus will result in large errors. In this paper, we
Xingbo Hu, Tian Xia, Leidong Yang, Fangming Wu, Yinghong Tian   +4 more
openaire   +2 more sources

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Graph Attention Neural Networks for Interpretable and Generalizable Prediction of Janus III–Vi Van Der Waals Heterostructures

Advanced Intelligent Discovery, EarlyView.
A crystal graph neural network based on the attention mechanism is proposed in this work. The model dynamically weights features through the attention mechanism, enabling precise prediction of properties of material from structural features. Here, taking Janus III–VI van der Waals heterostructures as a representative case, the properties have been ...
Yudong Shi, Zhao Zheng, Yinggan Zhang, Zhou Cui, Peng Lin, Cuilian Wen, Baisheng Sa, Zhimei Sun   +7 more
wiley   +1 more source

Accelerating Surface Composition Characterization of Thin‐Film Materials Libraries Using Multi‐Output Gaussian Process Regression

Advanced Intelligent Discovery, EarlyView.
To integrate surface analysis into materials discovery workflows, Gaussian process regression is used to accurately predict surface compositions from rapidly acquired volume composition data (obtained by energy‐dispersive X‐ray spectroscopy), drastically reducing the number of required surface measurements on thin‐film materials libraries.
Felix Thelen, Florian Lourens, Alfred Ludwig   +2 more
wiley   +1 more source

Down-Streaming Impact to the Competitiveness of Indonesia Cocoa

Khazanah Sosial
The objective of this paper is to provide qualitative and quantitative analysis on the competitiveness of Indonesia cocoa beans post down-streaming push by the Government of Indonesia.
Irfan Nabhani
doaj   +1 more source