Reset
Showing 20 of 1,017 academic articles

Development and web-based implementation of a machine learning model for predicting one-year adverse outcomes in acute ischaemic stroke

ChunYu Meng, FeiFei Zuo, Shuai Liu, YuLiang Ji et al. • Frontiers in Medicine (2026)

BackgroundThis study aimed to develop an interpretable and clinically applicable machine learning prediction model to assess the risk of adverse outcomes within one year following acute ischaemic stroke, and to establish a corresponding web...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2026.1956859

Portable NIR Spectroscopy Combined with Machine Learning for Kiwi Ripeness Classification: An Approach to Precision Farming

Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand, Francesco Genovese et al. • Applied Sciences (2025)

This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectr...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15116233

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

PosturAll: A Posture Assessment Software for Children

Ana Beatriz Neves, Rodrigo Martins, Nuno Matela, Tiago Atalaia • Bioengineering (2023)

From an early age, people are exposed to risk factors that can lead to musculoskeletal disorders like low back pain, neck pain and scoliosis. Medical screenings at an early age might minimize their incidence. The study intends to improve a ...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering10101171

Machine Learning in Medicine

Alvin Rajkomar, Jay B. Dean, Isaac S. Kohane • New England Journal of Medicine (2019)

Interview with Dr. Isaac Kohane on machine learning in medicine. (16:31)Download In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar pati...

OPENALEX DOI: https://doi.org/10.1056/nejmra1814259

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

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

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

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

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

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science (2022)

The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...

DOAJ Open Access (DOAJ) DOI: 10.5194/os-18-1491-2022

Design and Pilot Feasibility of a Low-Cost Wearable for Mexican Sign Language in Inclusive Higher Education

Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies (2026)

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies14030189

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

Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno, Antonio Brunetti et al. • IEEE Access (2023)

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3271748

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

Johannes Leiner, Vincent Pellissier, Sebastian König, Sven Hohenstein et al. • Respiratory Research (2022)

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12931-022-02180-w