Results 41 to 50 of about 25,341,143 (317)

Influence of Composition and Process Parameters on Aluminide Coatings Thickness: An Explainable Machine Learning-Assisted Approach [PDF]

Iranian Journal of Materials Science and Engineering
Aluminide coatings are widely used in high-temperature applications due to their excellent corrosion resistance and thermal stability. However, optimizing their composition and thickness is crucial for enhancing performance under varying operational ...
ali azari beni, Saeed Rastegari
doaj  

Explainable Ensemble Learning for Maternal Health Risk in Low-Resource Settings

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Maternal health remains a global challenge, particularly in low-resource settings where accurate and timely risk prediction is essential to reducing maternal mortality. This study proposes an explainable machine learning framework for predicting maternal
Lilik Widyawati, Neny Sulistianingsih
doaj   +1 more source

NATIONAL STATUSES GRANTED FOR PROTECTION REASONS IN IRELAND. ESRI RESEARCH SERIES NUMBER 96 January 2020 [PDF]

, 2020
This study examines the national statuses that may be granted for protection reasons in Ireland. The report focuses on national statuses with a sole basis in Irish domestic law and policy and does not examine in detail EU-harmonised statuses.
Brazil, Patricia, Groarke, Sarah
core  

Evaluating the Utilities of Foundation Models in Single‐Cell Data Analysis

Advanced Science, EarlyView.
This study delivers the first systematic, task‐level evaluation of single‐cell foundation models across eight core analytical tasks. By benchmarking 10 leading models with the scEval framework, it reveals where foundation models truly add value, where task‐specific methods still dominate, and provides concrete, reproducible guidelines to steer the next
Tianyu Liu, Kexing Li, Yuge Wang, Hongyu Li, Hongyu Zhao   +4 more
wiley   +1 more source

Association between green space coverage and dyslipidemia in adults: Combined with interpretable machine learning SHAP methods

环境与职业医学
BackgroundResearch on the association between dyslipidemia and green space coverage remains limited, and existing methods too rely on traditional fixed models to fully reveal the complex and nonlinear relationships and their interactions in large ...
Shiqi HUANG, Kehan ZHONG, Peizheng LI, Lu MA   +3 more
doaj   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Differentiated impacts of urban streetscapes on green mobility experiences

Journal of Asian Architecture and Building Engineering
Against the backdrop of accelerating urbanization and the growing emphasis on healthy city development, understanding the differentiated impacts of street spatial environments on human mobility and their perceived friendliness is essential for ...
Wangyao Jiang, Qingqing Li, Junjie Li, Zunling Zhu   +3 more
doaj   +1 more source

OSL Characterisation of Two Fluvial Sequences of the River Usmacinta in its Middle Catchment (SE Mexico) [PDF]

, 2014
The report summarizes luminescence profiling, initially using a SUERC PPSL system in Mexico, and laboratory analysis at SUERC, used to characterise the stratigraphy and interpret sedimentary processes in terrace deposits of the Usumacinta River, SE ...
Castillo Rodriguez, Miguel, Cruz-Zaragoza, Epifanio, Kinnaird, Tim C., Muñoz-Salinas, Esperanza, Sanderson, David C.W.   +4 more
core  

A Comparative Analysis of LIME and SHAP Interpreters With Explainable ML-Based Diabetes Predictions

IEEE Access
Explainable artificial intelligence is beneficial in converting opaque machine learning models into transparent ones and outlining how each one makes decisions in the healthcare industry.
Shamim Ahmed, M. Shamim Kaiser, Mohammad Shahadat Hossain, Karl Andersson   +3 more
semanticscholar   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source