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Development of a Transfer Learning Technique for Rapid Adaptation of Thermal Compensation Models to Long-Term Machine Thermal Behavior Changes

Chia-Chin Chuang, Zheng-Wei Lin Chi, Tzu-Chien Kuo, Che-Jui Chang et al. • Machines (2026)

Structural aging and environmental changes associated with long-term operation can substantially modify the thermal behavior of machine tools, diminishing the accuracy of existing thermal compensation models. Traditional neural network appr...

DOAJ Open Access (DOAJ) DOI: 10.3390/machines14030309

Prediction of Drug Targets for Specific Diseases Leveraging Gene Perturbation Data: A Machine Learning Approach

Kai Zhao, Yujia Shi, Hon-Cheong So • Pharmaceutics (2022)

Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles fro...

DOAJ Open Access (DOAJ) DOI: 10.3390/pharmaceutics14020234

Quantifying the incremental value of deep learning: Application to lung nodule detection.

Theodore Warsavage, Fuyong Xing, Anna E Barón, William J Feser et al. • PLoS ONE (2020)

We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0231468

Machine learning-assisted three-dimensional mapping of the facial soft tissues in Saudi Arabian adults with skeletal class I relationship

Nora Alhazmi, Rana Almazroa, Muhannad Alshehri, Saad Bin Shabib et al. • Journal of Orthodontic Science (2026)

OBJECTIVES: This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...

DOAJ Open Access (DOAJ) DOI: 10.4103/jos.jos_111_25

Probabilistic daily runoff forecasting in high-altitude cold regions using a hybrid model combining DBO and transformer variants

Qiying Yu, Wenzhong Li, Yungang Bai, Zhenlin Lu et al. • Journal of Hydrology: Regional Studies (2025)

Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° t...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ejrh.2025.102311

Machine Learning in Medical Imaging

Miles N. Wernick, Yongyi Yang, Jovan G. Brankov, Grigori Yourganov et al. • IEEE Signal Processing Magazine (2010)

This article will discuss very different ways of using machine learning that may be less familiar, and we will demonstrate through examples the role of these concepts in medical imaging. Although the term machine learning is relatively rece...

OPENALEX Open Access DOI: https://doi.org/10.1109/msp.2010.936730 PMC: 4220564

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

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

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

Machine Learning for Medical Imaging

Bradley James Erickson, Panagiotis D. Korfiatis, Zeynettin Akkus, Timothy Lee Kline • Radiographics (2017)

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the ma...

OPENALEX Open Access DOI: https://doi.org/10.1148/rg.2017160130 PMC: 5375621

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Prashant D. Tailor, MD, Piotr K. Kopinski, MD, PhD, Haley S. D’Souza, MD, David A. Leske, MS et al. • Ophthalmology Science (2025)

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.xops.2024.100584