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Showing 20 of 127 academic articles

The Microbiome Composition of a Man's Penis Predicts Incident Bacterial Vaginosis in His Female Sex Partner With High Accuracy

Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology (2020)

Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcimb.2020.00433

Using fuzzy and machine learning iterative optimized models to generate the flood susceptibility maps: case study of Prahova River basin, Romania

Romulus Costache, Hazem Ghassan Abdo, Arun Pratap Mishra, Subodh Chandra Pal et al. • Geomatics, Natural Hazards & Risk (2023)

AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...

DOAJ Open Access (DOAJ) DOI: 10.1080/19475705.2023.2281241

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE (2024)

Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0314959

Kernel methods in machine learning

Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola • The Annals of Statistics (2008)

We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a ke...

OPENALEX Open Access DOI: https://doi.org/10.1214/009053607000000677

Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction

Alejandro Casallas, Camila Jiménez-Saenz, Victor Torres, Miguel Quirama-Aguilar et al. • Sensors (2022)

Throughout the years, wildfires have negatively impacted ecological systems and urban areas. Hence, reinforcing territorial risk management strategies against wildfires is essential. In this study, we built an early alert system (EAS) with ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22228790

Cybersecurity in Smart Grids: Detecting False Data Injection Attacks Utilizing Supervised Machine Learning Techniques

Anwer Shees, Mohd Tariq, Arif I. Sarwat • Energies (2024)

By integrating advanced technologies and data-driven systems in smart grids, there has been a significant revolution in the energy distribution sector, bringing a new era of efficiency and sustainability. Nevertheless, with this advancement...

DOAJ Open Access (DOAJ) DOI: 10.3390/en17235870

A State-of-the-Art Review on Machine Learning-based Methods for Prostate Cancer Diagnosis

Ari Mohammed ali Ahmed, Aree Ali Mohammed, Professor • UHD Journal of Science and Technology (2021)

Prostate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both bi...

DOAJ Open Access (DOAJ) DOI: https://doi.org/10.21928/uhdjst.v5n2y2021.pp41-47

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117

Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain?

Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce, Jeffrey Bolton et al. • Algorithms (2023)

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images i...

DOAJ Open Access (DOAJ) DOI: 10.3390/a16120567

Machine Learning in Virtual Screening

James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening (2009)

In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...

OPENALEX DOI: https://doi.org/10.2174/138620709788167980

Benchmarking Supervised Classifiers for Concurrent Multidomain Dropout-Intention Attributions in Higher Education: Evidence from a Colombian Public University

Marieth Agnes Guillen-García, Osnamir Elias Bru-Cordero, Cristian David Correa-Álvarez • Big Data and Cognitive Computing (2026)

Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...

DOAJ Open Access (DOAJ) DOI: 10.3390/bdcc10080274

Virtual CT Myelography: A Patch-Based Machine Learning Model to Improve Intraspinal Soft Tissue Visualization on Unenhanced Dual-Energy Lumbar Spine CT

Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information (2022)

Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...

DOAJ Open Access (DOAJ) DOI: 10.3390/info13090412

An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

USMAN, A., CHOUDHRY, M. A. • Advances in Electrical and Computer Engineering (2021)

Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails due to power disturbance (PD). A fast and accurate PD detection method is required to ensure trans...

DOAJ Open Access (DOAJ) DOI: 10.4316/AECE.2021.02010

Introduction to Machine Learning

Arvind Kumar Tiwari • IGI Global eBooks (2019)

Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...

OPENALEX DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003

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

Interactive machine learning

Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI) (2003)

Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...

OPENALEX DOI: https://doi.org/10.1145/604045.604056