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Feature Selection and Rule Generation Integrated Learning for Takagi-Sugeno-Kang Fuzzy System and its Application in Medical Data Classification

Xiaoqing Gu, Cong Zhang, Tongguang Ni • IEEE Access (2019)

The rule-based fuzzy systems have successfully applied for numerous medical data classification problems. However, structuring the concise and interpretable fuzzy rules with good classification performance is still a big challenge. To addre...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2954707

The relationship between perceived outdoor sports atmosphere and social-emotional competence among college students: the mediating role of core self-evaluation and the moderating role of digital health literacy

Junhong Cui, Namei Song, Xiaobei Gu, Shawei Zhang • Frontiers in Psychology (2026)

ObjectiveThis study aims to explore the relationship between the perceived outdoor sports atmosphere and social-emotional competencies among college students, with a focus on examining the mediating role of core self-evaluation and the mode...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyg.2026.1947247

Identification of confounders and estimating the causal effect of place of birth on age-specific childhood vaccination

Ashagrie Sharew Iyassu, Haile Mekonnen Fenta, Zelalem G. Dessie, Temesgen T. Zewotir • BMC Medical Informatics and Decision Making (2024)

Abstract Background In causal analyses, some third factor may distort the relationship between the exposure and the outcome variables under study, which gives spurious results. In this case, treatment groups and control groups that receive ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02827-2

Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications

Mohammad Aldossary, Ibrahim Alzamil, Jaber Almutairi • Drones (2025)

Due to Internet of Drones (IoD) technology, drone networks have proliferated, transforming surveillance, logistics, and disaster management. Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities i...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones9010046

The relationship between perceived stress and depression in colorectal cancer patients: the mediating role of illness perception and the moderating role of self-efficacy

Fuzhuo Wang, Jiashuang Xu, Hong Sun, Xiuli Wang et al. • Frontiers in Oncology (2026)

BackgroundNumerous studies have demonstrated a close association between perceived stress and depression in colorectal cancer patients; however, the underlying mechanisms remain incompletely understood. This study aims to investigate the im...

DOAJ Open Access (DOAJ) DOI: 10.3389/fonc.2026.1746202

Predicting Microbial Protein Synthesis in Cattle: Evaluation of Extant Equations and Steps Needed to Improve Accuracy and Precision of Future Equations

Michael L. Galyean, Luis O. Tedeschi • Animals (2024)

Predictions of microbial crude protein (MCP) synthesis for beef cattle generally rely on empirical regression equations, with intakes of energy and protein as key variables. Using a database from published literature, we developed new equat...

DOAJ Open Access (DOAJ) DOI: 10.3390/ani14192903

Computer Vision and Pattern Recognition 2020

Zeynep Akata, Andreas Geiger, Torsten Sattler • International Journal of Computer Vision (2021)

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-021-01522-3

Boosting Neural Networks

Holger Schwenk, Yoshua Bengio • Neural Computation (2000)

Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, AdaBoost, has been applied with great success to several benchmark machine learning problems using mainly decision tr...

OPENALEX DOI: https://doi.org/10.1162/089976600300015178

A Review of Deep Learning Applications in Intrusion Detection Systems: Overcoming Challenges in Spatiotemporal Feature Extraction and Data Imbalance

Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences (2025)

In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15031552

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China

Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports (2025)

Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-19922-7

Application of Machine Learning for Predicting Progression‐Free and Overall Survival in Patients With Renal Cell Carcinoma

Caroline W. Grant, Jerry Li, Swan Lin, Dana Nickens et al. • Clinical and Translational Science (2025)

ABSTRACT Patient outcomes in advanced renal cell carcinoma (RCC) remain poor, with five‐year survival rates ranging from ~10% to 30%. Early projections of therapeutic outcomes could optimize precision medicine and accelerate drug developmen...

DOAJ Open Access (DOAJ) DOI: 10.1111/cts.70348

Epistemic frontiers and the distinction between causality, information, and predictability in pattern recognition

Pablo Neirz, Héctor Allende, Carolina Saavedra • Scientific Reports (2026)

Abstract High predictive accuracy is frequently misinterpreted as evidence of causal understanding or population-level signal. Models can exploit spurious correlations, confounding, or protocol-induced artefacts, while post-hoc explanations...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-52883-z

Stacking Ensemble Approach for Churn Prediction: Integrating CNN and Machine Learning Models with CatBoost Meta-Learner

Tan Yan Lin, Pang Ying Han, Ooi Shih Yin, Khoh Wee How et al. • Journal of Engineering Technology and Applied Physics (2023)

In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...

DOAJ Open Access (DOAJ) DOI: 10.33093/jetap.2023.5.2.12

mlr: Machine Learning in R

Bernd Bischl, Michel Lang, Lars Kotthoff, Patrick Schratz et al. (2013)

Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensiti...

OPENALEX Open Access DOI: https://doi.org/10.32614/cran.package.mlr

Hands-On Machine Learning with R

Brad Boehmke, Brandon Greenwell • Chapman & Hall/CRC eBooks (2019)

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process a...

OPENALEX DOI: https://doi.org/10.1201/9780367816377

Detection and Classification of Abnormities of First Heart Sound Using Empirical Wavelet Transform

Haixia Li, Yongfeng Ren, Guojun Zhang, Renxin Wang et al. • IEEE Access (2019)

It is expected that an automatic detection and classification algorithm for the abnormities of first heart sound (S1) can realize computer artificial intelligence diagnosis of some relative cardiovascular disease. Few studies have focused o...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2943705