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Showing 20 of 74 academic articles

Artificial intelligence for pediatric height prediction using large-scale longitudinal body composition data

Dohyun Chun, Hae Woon Jung, Jongho Kang, Woo Young Jang et al. • Digital Health (2025)

Objective We developed a precise, reliable artificial intelligence (AI) model for predicting the future height of children and adolescents based on anthropometric and body composition data. Materials and Methods We used an extensive longitu...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076251395975

Power Load Probabilistic Prediction Based on Multi-Value Quantile Regression and Timing Fusion Ensemble Learning Model

Yuhang Liu, Fei Mei, Jun Zhang, Xiang Dai et al. • Entropy (2026)

The core component to ensure the refined and safe operation of distribution network scheduling is 10 kV bus load probabilistic prediction. However, existing probabilistic prediction methods suffer from insufficient dynamic feature extractio...

DOAJ Open Access (DOAJ) DOI: 10.3390/e28030329

Evaluating key predictors of breast cancer through survival: a comparison of AFT frailty models with LASSO, ridge, and elastic net regularization

Senyefia Bosson-Amedenu, Emmanuel Ayitey, Francis Ayiah-Mensah, Luyton Asare • BMC Cancer (2025)

Abstract Background Frailty models are extensively utilized in survival analysis to address unobserved heterogeneity among individuals. However, selecting the most robust model for survival prediction, especially in the context of high-dime...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12885-025-14040-z

Metabolomic sweet spot clock predicts mortality and age-related diseases in the Canadian Longitudinal Study on Aging

Olga Vishnyakova, Joosung Min, Stephen Leach, Xiaowei Song et al. • Communications Medicine (2026)

Abstract Background Chronological age does not capture individual health or resilience. Advances in metabolomics have enabled development of molecular aging biomarkers that capture deviations between biological and chronological age, highli...

DOAJ Open Access (DOAJ) DOI: 10.1038/s43856-026-01375-2

A robust and uncertainty-aware machine learning framework for PM2.5 prediction in a coastal urban Indian environment: implications for sustainable air quality management

Salvator Lawrence, Srimuruganandam Bhathmanabhan • Sustainable Environment Research (2026)

Abstract Accurate prediction of fine particulate matter (PM2.5) remains challenging because atmospheric processes are nonlinear, nonstationary, and influenced by temporal variability, measurement uncertainty, and episodic pollution events. ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42834-026-00296-y

Molecular Informatics, Chemometrics, and Sensory Omics for Constructing an Umami Peptide Cluster Library Across the Entire Lager Beer Brewing Process

Yashuai Wu, Ruiyang Yin, Wenjing Tian, Wanqiu Zhao et al. • Foods (2026)

Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, pep...

DOAJ Open Access (DOAJ) DOI: 10.3390/foods15040641

Deep learning-based multimodal data fusion in bone tumor management: Advances in clinical decision support

Tongtong Huo, Wei Wu, Xiaoliang Chen, Mingdi Xue et al. • Intelligent Oncology (2025)

Bone tumors (BTs)—including osteosarcoma, Ewing sarcoma, and chondrosarcoma—are rare but biologically complex malignancies characterized by pronounced heterogeneity in anatomical location, histological subtype, and molecular alterations. Re...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.intonc.2025.06.005

Argumentation approaches for explanaible AI in medical informatics

Luciano Caroprese, Eugenio Vocaturo, Ester Zumpano • Intelligent Systems with Applications (2022)

Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are often considered black boxes as they do not provide any explanation about how outputs are derived from inputs or why a decision is taken. There...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.iswa.2022.200109

Adaptive frequency band attention-guided CNN–BiLSTM for Spatial–Spectral–Temporal EEG emotion recognition

Rabita Hasan, Sheikh Md. Rabiul Islam • Brain Informatics (2026)

Abstract Electroencephalography (EEG)-based emotion recognition has gained increasing attention in affective computing because EEG provides high temporal resolution and reflects intrinsic neural activity. However, reliable emotion recogniti...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40708-026-00319-9

Fundus imaging based quantum computing: Grading of severity of vision threatening diabetic retinopathy

Amna Ikram, Azhar Imran • Informatics in Medicine Unlocked (2026)

Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accura...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.imu.2026.101744

Explainable AI for Cybersecurity

Siva Raja Sindiramutty, Chong Eng Tan, Sei Ping Lau, Rajan Thangaveloo et al. • Advances in computational intelligence and robotics book series (2024)

In recent years, the utilization of AI in the field of cybersecurity has become more widespread. Black-box AI models pose a significant challenge in terms of interpretability and transparency, which is one of the major drawbacks of AI-based...

OPENALEX DOI: https://doi.org/10.4018/978-1-6684-6361-1.ch002

A Survey on Neural Network Interpretability

Yu Zhang, Peter Tiňo B, Aleš Leonardis, Ke Tang • IEEE Transactions on Emerging Topics in Computational Intelligence (2021)

Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g.,...

OPENALEX Open Access DOI: https://doi.org/10.1109/tetci.2021.3100641

On Interpretability of Artificial Neural Networks: A Survey

Fenglei Fan, Jinjun Xiong, Mengzhou Li, Ge Wang • IEEE Transactions on Radiation and Plasma Medical Sciences (2021)

Deep learning as represented by the artificial deep neural networks (DNNs) has achieved great success recently in many important areas that deal with text, images, videos, graphs, and so on. However, the black-box nature of DNNs has become ...

OPENALEX Open Access DOI: https://doi.org/10.1109/trpms.2021.3066428 PMC: 9105427

Interpretable and Explainable Machine Learning for Materials Science and Chemistry

Felipe Oviedo, Juan Lavista Ferres, Tonio Buonassisi, Keith T. Butler • Accounts of Materials Research (2022)

High Resolution Image Download MS PowerPoint Slide Conspectus Machine learning has become a common and powerful tool in materials research. As more data become available, with the use of high-performance computing and high-throughput experi...

OPENALEX cc-by DOI: https://doi.org/10.1021/accountsmr.1c00244

Coalition of explainable artificial intelligence and quantum computing in precision medicine

Soumyadeep Ray, Pronaya Bhattacharya, Ebrahim A. Mattar, Abhishek Mukhopadhyay • Computational and Structural Biotechnology Journal (2025)

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning model...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.csbj.2025.11.031

An Explainable AI-Driven Zero-Day Attack Detection Framework for Securing Edge Devices in Smart Cities

Santhiyakumari N., Sabarinathan S., Veerakumar S., Chandraman M. et al. • Journal of Cognitive Human-Computer Interaction (2025)

The rapid proliferation of edge computing in smart cities has enhanced real-time data processing capabilities, but it has also exposed critical vulnerabilities to sophisticated cyber threats such as zero-day attacks. Traditional signature-b...

DOAJ Open Access (DOAJ) DOI: 10.54216/JCHCI.100201

A Unified Transformer–BDI Architecture for Financial Fraud Detection: Distributed Knowledge Transfer Across Diverse Datasets

Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro • Forecasting (2025)

Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow...

DOAJ Open Access (DOAJ) DOI: 10.3390/forecast7020031

Improved Immunohistochemistry of Mouse Eye Sections Using Davidson's Fixative and Melanin Bleaching

Anne Longakit, Chloe Hess, Christina Zhang, Catherine Van Raamsdonk • Bio-Protocol (2025)

Immunohistochemistry (IHC) and immunofluorescence (IF) are fundamental molecular biology techniques to assess protein expression. However, the melanin present normally in the eye in the uveal tract (choroid, iris, and ciliary body) and the ...

DOAJ Open Access (DOAJ) DOI: 10.21769/BioProtoc.5510

QG-WRN: A Quantum-Enhanced Graph Convolutional Wide Residual Network for ASD Diagnosis via Neuroimaging Sensing Technology

Nanting Huang, Xiaoyu Li, Xin Yang, Li Xie et al. • Sensors (2026)

The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by adva...

DOAJ Open Access (DOAJ) DOI: 10.3390/s26133997