Results 121 to 130 of about 91,735 (266)

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

A STUDY ON MACHINE LEARNING-BASED APPROACHES FOR EARLY DETECTION OF PARKINSON’S DISEASE

Tạp chí Khoa học
Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the gradual loss of dopaminergic neurons in the brain, leading to both motor and non-motor symptoms.
Tran Thi Huong
doaj   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

A Machine Learning Approach to Spatial Analysis of Paddy Field Conversion Using Multispectral Sentinel-2A Imagery

JOIV: International Journal on Informatics Visualization
The expanse of rice fields is a critical metric as it is intimately linked to agricultural productivity in a given locale. This study investigates the application of satellite imagery to quantify trice fields' acreage and temporal variations.
Achmad Fauzan, Anang Kurnia
doaj   +1 more source

A Data‐Centric Approach to Quantifying the Forward and Inverse Relationship Between Laser Powder Bed Fusion Process Parameters and as‐Built Surface Roughness of IN718 Parts

Advanced Intelligent Systems, EarlyView.
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley   +1 more source

Time Series Forecasting of MSCI Indices With Machine Learning

Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Machine learning has become an increasingly important tool for understanding the dynamic nature of financial markets and predicting future price movements.
Mehmet Ali Cengiz, Diler Türkoğlu
doaj   +1 more source

Stroke Prediction Using XGboost and a Fusion of XGboost with Random Forest

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Abstract - Stroke is a life-threatening medical condition caused by disrupted blood flow to the brain, representing a major global health concern with significant health and economic consequences. Researchers are working to tackle this challenge by developing automated stroke prediction algorithms, which can enable timely interventions and potentially ...
openaire   +1 more source

Further Detail Concerning the Deep Learning Model for Mortality After Total Gastrectomy

Annals of Gastroenterological Surgery, EarlyView.
Kentaro Goto, Haruku Fujita, Ryohei Onishi, Nobuaki Hoshino, Koya Hida   +4 more
wiley   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

Universal Catalyst Design Framework for Electrochemical Hydrogen Peroxide Synthesis Facilitated by Local Atomic Environment Descriptors

Angewandte Chemie, EarlyView.
A universal catalyst design framework integrating weighted atom‐centered symmetry function (wACSF) descriptors with machine learning accurately predicts adsorption energies for 2e− water oxidation reaction. Microkinetic modeling and experimental validation confirm the framework's universality, establishing a powerful paradigm for rational ...
Zhijian Liu, Yan Liu, Yuqi Zhang, Yeyu Deng, Zhong Zheng, Ruth Knibbe, Tianxiang Gao, Mingzhe Li, Ziye Wang, Bingqian Zhang, Xue Jia, Di Zhang, Heng Liu, Xuqiang Shao, Zhengyang Gao, Li Wei, Hao Li, Weijie Yang   +17 more
wiley   +2 more sources