Results 31 to 40 of about 29,456 (261)

Rapid diagnosis of Helicobacter pylori infection status based on endoscopic features and deep learning algorithms

Frontiers in Public Health
Background and aimsEndoscopic visualization for the diagnosis of Helicobacter pylori (HP) infection status is highly important for helping endoscopists quickly understand the status of gastric background mucosa and assisting in subsequent diagnosis and ...
Xinying Yu, Lianyu Li, Qiang He
doaj   +1 more source

Machine learning-based assessment of the impact of biochar amendment on plant productivity in salt-affected soils [PDF]

E3S Web of Conferences
Soil salinization is one of the major environmental problems facing the world at present, and its negative impact on agricultural production and ecological balance is increasingly prominent.
Mao Zhenxuan, Chen Kun, Liu Qiang, Xu Mengjiao   +3 more
doaj   +1 more source

Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea, Patrick Ellsworth, James E. Siegler, James R. Brorson, Christina M. Lineback, Frank G. Conyers, Deborah Kerrigan, Kelsey Eklund, Shadi Yaghi, Farid Khasiyev, Emiliya Melkumova, Collin J. Culbertson, Marissa D'Souza, Dinesh V. Jillella, Patrick Glover, Hassan Aboul‐Nour, Fadi Nahab, Mahan Shahrivari, Simona Nedelcu, David S. Liebeskind, Matthew M. Smith, Aaron Rothstein, Anna Bowman, Alicia Zha, Narendra Kala, Ahmad Abu Qdais, Sami Al Kasab, Mudassir Farooqui, Diana Rojas‐Soto, Yasmin Aziz, Franziska Herpich, Jean‐Philippe Daniel, Sean L. Thompson, Vivek Patel, Thanh N. Nguyen, Siddharth Sehgal, Wenzheng Yu, Wayneho Kam, Russel Van Coevering, Oana M. Dumitrascu, Muhammad Alvi, Balaji Krishnaiah, Setareh Salehi Omran, Guillermo Linares, Eesha Singh, Hamid Ali, Mary Penckofer, Jesse M. Thon, Shani Mannion, Dalia Chahien, Lucia Chen, Fawad Talat, Mehdi Abbasi, Richa Sharma   +53 more
wiley   +1 more source

A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes

Sakarya University Journal of Computer and Information Sciences
Integrating Industry 4.0 (I4.0) technologies into warehouse management critically enhances strategic performance. However, existing studies often overlook the causal relationships between strategic outcomes and the transparency of technology ...
Ahmet Kala, Cem Özkurt, Bilal Emre Yahyaoğlu   +2 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

ANN model for prediction of thermo-hydraulic performance of a solar air heater with vertical cylindrical ribs

Energy Reports, 2022
A hybrid computational fluid dynamics-artificial neural network approach is applied to predict the thermo-hydraulic performance factor (THPF) of a solar air heater with vertical cylindrical ribs.
Sarvapriya Singh, Siddharth Suman, Santanu Mitra, Manish Kumar   +3 more
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

A Feature Selection Method for Yarn Quality Prediction Based on SHAP Interpretation

Algorithms
This study developed an interpretable framework, RFE-SHAP, designed for yarn quality prediction. It integrates Recursive Feature Elimination (RFE) with SHapley Additive exPlanations (SHAP) theory to refine feature selection and mitigate data redundancy ...
Chunxue Wei, Tianxiang Liu, Baowei Zhang, Xiao Wang   +3 more
doaj   +1 more source

Machine learning-driven predictive models for compressive strength of steel fiber reinforced concrete subjected to high temperatures

Case Studies in Construction Materials, 2023
Steel-fiber-reinforced concrete (SFRC) has emerged as a viable and efficient substitute for traditional concrete in the construction industry. By incorporating steel fibers into the concrete mixture, SFRC offers enhanced crack resistance, improved post ...
Rayed Alyousef, Muhammad Faisal Rehman, Majid Khan, Muhammad Fawad, Asad Ullah Khan, Ahmed M. Hassan, Nivin A. Ghamry   +6 more
doaj   +1 more source

Functionalizing Micro‐to‐Mesoscopic Electrode Architectures for Regulating Electron Transfer Behaviors in Electrocatalysis

Advanced Functional Materials, EarlyView.
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao, Jiaojiao Zhang, Shideng Yuan, Xinmeng Yu, Keming Wan, Xiaoguang Duan, Zhining Wang   +6 more
wiley   +1 more source