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A flexible analytic wavelet transform and ensemble bagged tree model for electroencephalogram-based meditative mind-wandering detection

Ajay Dadhich, Jaideep Patel, Rovin Tiwari, Richa Verma et al. • Healthcare Analytics (2024)

Mind-wandering (MW) is when an individual’s concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100286

A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies (2023)

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...

DOAJ Open Access (DOAJ) DOI: 10.3390/en16114271

Machine learning approach for the estimation of missing precipitation data: a case study of South Korea

Heechan Han, Boran Kim, Kyunghun Kim, Donghyun Kim et al. • Water Science and Technology (2023)

Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an ...

DOAJ Open Access (DOAJ) DOI: 10.2166/wst.2023.237

Computer Vision-Based Assessment of Motor Functioning in Schizophrenia: Use of Smartphones for Remote Measurement of Schizophrenia Symptomatology

Anzar Abbas, Vijay Yadav, Emma Smith, Elizabeth Ramjas et al. • Digital Biomarkers (2021)

Introduction: Motor abnormalities have been shown to be a distinct component of schizophrenia symptomatology. However, objective and scalable methods for assessment of motor functioning in schizophrenia are lacking. Advancements in machine ...

DOAJ Open Access (DOAJ) DOI: 10.1159/000512383

Comparing Clinical Metadata Fusion Strategies for Diabetic and Hypertensive Retinopathy Classification

Vinicius de Carvalho Rispoli, Alan Müller, Weverson Garcia Medeiros, Marília Miranda Forte Gomes et al. • Machine Learning and Knowledge Extraction (2026)

Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...

DOAJ Open Access (DOAJ) DOI: 10.3390/make8100299

Discovering subtypes with imaging signatures in the Motoric Cognitive Risk Syndrome Consortium using weakly supervised clustering

Bhargav Teja Nallapu, Ali Ezzati, Helena M. Blumen, Kellen K. Petersen et al. • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

ABSTRACT INTRODUCTION Understanding the heterogeneity of brain structure in individuals with the Motoric Cognitive Risk Syndrome (MCR) may improve the current risk assessments of dementia. METHODS We used data from six cohorts from the MCR ...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70197

Towards instance-wise calibration: local amortized diagnostics and reshaping of conditional densities (LADaR)

Biprateep Dey, David Zhao, Brett H Andrews, Jeffrey A Newman et al. • Machine Learning: Science and Technology (2025)

Key science questions, such as galaxy distance estimation and weather forecasting, often require knowing the full predictive distribution of a target variable Y given complex inputs X . Despite recent advances in machine learning and physic...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/ae1f05

Machine Learning for Sociology

Mario D. Molina, Filiz Garip • Annual Review of Sociology (2019)

Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev-soc-073117-041106

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

Machine Learning for Fluid Mechanics

Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos • Annual Review of Fluid Mechanics (2019)

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev-fluid-010719-060214

Overfitting and undercomputing in machine learning

Thomas G. Dietterich • ACM Computing Surveys (1995)

suggests a reasonable line of research: find algorithms that can search the hypothesis class better. Hence, there is been extensive research in applying second-order methods to fit neural networks and in conducting much more thorough search...

OPENALEX Open Access DOI: https://doi.org/10.1145/212094.212114

Hybrid machine learning and 3D numerical modeling-based multi-objective optimization of geosynthetic-reinforced pile-supported embankments

Ammar Alnmr, Ammar Alnmr, Rashad Alsirawan, Haidar Hosamo et al. • Frontiers in Built Environment (2026)

Efficient and reliable design of Geosynthetic Reinforced Pile-Supported (GRPS) embankments on soft ground remains challenging due to the complex nonlinear soil–structure interaction and the high computational cost of repeated numerical anal...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbuil.2026.1829950

Improved railway track faults detection using Mel-frequency cepstral coefficient and constant-Q transform features

Rahman Shafique, Khadija Kanwal, Venkata Chunduri, Gyu Sang Choi et al. • Scientific Reports (2025)

Abstract Regular inspection of the health of railway tracks is crucial to maintaining reliable and safe train operations. Some factors including cracks, rail discontinuity, ballast issues, burn wheels, super-elevation, loose nuts and bolts,...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-14763-w

PCPAm - A dataset of histopathological images of penile cancer for classification tasksZenodo

Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida, Vandecia Rejane Monteiro Fernandes et al. • Data in Brief (2025)

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111823

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science (2025)

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

DOAJ Open Access (DOAJ) DOI: 10.30919/es1972

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science (2023)

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2023.1242201

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making (2024)

Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02652-7