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Showing 20 of 739 academic articles

Determinants of Tourism Demand Using Machine Learning Techniques

Musonera Abdou, Edouard Musabanganji, Herman Musahara • African Journal of Hospitality, Tourism and Leisure (2022)

The purpose of the current study was to determine factors affecting tourism demand using machine learning techniques. The results of different linear regression and random forest models on both the train and test sets were compared using RM...

DOAJ Open Access (DOAJ) DOI: https://doi.org/10.46222/ajhtl.19770720.256

Rapid Deployment of Deep Learning-Based Condition Monitoring for Rotating Machines

Aleksanteri Hamalainen, Aku Karhinen, Jesse Miettinen, Zacharias Dahl et al. • IEEE Access (2025)

Rotating machines are extremely common in many industries, and their maintenance involves substantial costs and labor. Most recent studies aiming to automate fault diagnosis have focused on deep learning, but industry adoption has been slow...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3627885

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing (2026)

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs18172862

Machine Learning in Medicine

Rahul C. Deo • Circulation (2015)

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular va...

OPENALEX Open Access DOI: https://doi.org/10.1161/circulationaha.115.001593 PMC: 5831252

Machine learning applications in epilepsy

Bardia Abbasi, Daniel M. Goldenholz • Epilepsia (2019)

Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...

OPENALEX Open Access DOI: https://doi.org/10.1111/epi.16333 PMC: 9897263

Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study

Qingfeng Sun, Kai Zhang, Yuanlong Xu, Mengmei Luo et al. • BMC Infectious Diseases (2025)

Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12879-025-11998-w

Integrated Bioinformatics Analysis and Experimental Verification of Immune Cell Infiltration and the Related Core Genes in Ulcerative Colitis

Zhao D, Qin D, Yin L, Yang Q • Pharmacogenomics and Personalized Medicine (2023)

Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...

DOAJ Open Access (DOAJ)

Machine learning for neuroimaging with scikit-learn

Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics (2014)

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....

OPENALEX cc-by DOI: https://doi.org/10.3389/fninf.2014.00014 PMC: 3930868

Bayesian Reasoning and Machine Learning

David Barber • Cambridge University Press eBooks (2012)

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511804779

Machine learning for precision medicine

Sarah J. MacEachern, Nils D. Forkert • Genome (2020)

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...

OPENALEX Open Access DOI: https://doi.org/10.1139/gen-2020-0131

Development of a Data-Based Machine Learning Model for Classifying and Predicting Property Damage Caused by Fire

Jongho Lee, Jiuk Shin, Jaewook Lee, Chorong Park et al. • Applied Sciences (2023)

Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage...

DOAJ Open Access (DOAJ) DOI: 10.3390/app132111866

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

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

Machine Learning in Action

Peter de B. Harrington (2012)

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

OPENALEX

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

Saiqing Chen, Chunxia Zhang, Yueting Yu • Frontiers in Cardiovascular Medicine (2025)

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2025.1625064

Multi-Resolution and Multi-Temporal Satellite Remote Sensing Analysis to Understand Human-Induced Changes in the Landscape for the Protection of Cultural Heritage: The Case Study of the MapDam Project, Syria

Nicodemo Abate, Diego Ronchi, Sara Elettra Zaia, Gabriele Ciccone et al. • Land (2025)

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...

DOAJ Open Access (DOAJ) DOI: 10.3390/land14112233