Results 91 to 100 of about 36,209 (267)

Comparative Analysis of Random Forest and XGBoost Models for Cervical Cancer Risk Prediction using SHAP-based Explainable AI

Journal of Applied Informatics and Computing
Cervical cancer remains one of the leading causes of cancer-related deaths among women, particularly in developing countries such as Indonesia. This study aims to develop an accurate and interpretable predictive model for cervical cancer risk using ...
Muhammad Agung Reza Yudha, Majid Rahardi
doaj   +1 more source

CS-SHAP: Extending SHAP to cyclic-spectral domain for better interpretability of intelligent fault diagnosis

Mechanical Systems and Signal Processing
21 pages, 21 ...
Qian Chen, Xingjian Dong, Kui Hu, Kangkang Chen, Zhike Peng, Guang Meng   +5 more
openaire   +2 more sources

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

Machine learning ensemble models for predicting the antibacterial efficacy of gold nanoparticles

Materials Research Express
Antimicrobial resistance (AMR) has been increasing rapidly, emerging as a major global health challenge. Gold nanoparticles (AuNPs) are promising antibacterial agents due to their biocompatibility, low toxicity, and ease of functionalization.
Priya Mary, A Mujeeb
doaj   +1 more source

The Role of Financial Markets in Predicting BIST Sustainability Index Performance: New Evidence from Hybrid Machine Learning Models

Ekonomi, Politika & Finans Araştırmaları Dergisi
The increasing importance of sustainable finance makes it critical to understand and accurately model the performance dynamics of investment instruments in this area. This study aims to forecast the return of the BIST Sustainability Index using financial
Zeynep Çolak
doaj   +1 more source

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, EarlyView.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source

A Transparent AI-Driven Multiclass Decision Support System for Thyroid Risk Prediction Using Machine Learning and Deep Learning Approaches

Foundations of Computing and Decision Sciences
Early and accurate diagnosis of thyroid disorders is essential due to their prevalence and health impact. To enhance interpretability in clinical settings, we propose a comprehensive workflow for transparent thyroid disease prediction using a multiclass ...
Ouartani Siouar, Taleb Nora
doaj   +1 more source

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

Advanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun, S. M. Rifatur Rana, Md. Golam Morshed, Imrose Jahan, F. A. Sabbir Ahamed, Md. Jahedul Islam   +5 more
wiley   +1 more source

Market Value Tier Classification of Indonesian Football Players using Ensemble Machine Learning and SHAP Analysis

Jurnal Teknologi dan Manajemen Informatika
The persistent discrepancy between actual transfer fees and the theoretical market values of football players highlights the need for a more objective and data-driven framework for player valuation.
Cinantya Paramita, Malfino Wildan Akhya, Pulung Nurtantio Andono   +2 more
doaj   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source