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Showing 20 of 1,380 academic articles

Burnout Risk Profiles in Psychology Students: An Exploratory Study with Machine Learning

M. Graça Pereira, Martim Santos, Renata Magalhães, Cláudia Rodrigues et al. • Behavioral Sciences (2025)

University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...

DOAJ Open Access (DOAJ) DOI: 10.3390/bs15040505

A diagnostic model based on clinical indicators and radiomics features for superior labral anterior and posterior lesions in the shoulder joint

Hongyu Wang, Lin Wang, Lei Shi, Fei Wang et al. • Journal of Orthopaedic Surgery (2026)

Background Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Accurate diagnosis remains challenging in clinical practice. This study aims to develop and evaluate radiomics models and ...

DOAJ Open Access (DOAJ) DOI: 10.1177/10225536261418429

Source apportionment and stochastic evaluation of soil contamination and human health risks of potentially toxic elements in Nangodi, northern Ghana

Samuel Dzidefo Sagoe, Raymond Webrah Kazapoe, Daniel Kwayisi, Seidu Alidu et al. • Discover Soil (2026)

Abstract Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an int...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44378-026-00229-6

Machine Learning in Healthcare

Hafsa Habehh, Suril Gohel • Current Genomics (2021)

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...

OPENALEX Open Access DOI: https://doi.org/10.2174/1389202922666210705124359 PMC: 8822225

Dynamic Monitoring of Thyroid-Stimulating Hormone Receptor Antibody and Extraocular Muscle Thickness: A Clinical Risk Stratification Model for Recurrence Risk Post-Glucocorticoid Therapy in TED Patients

Li Y, Yang X, Hu S • International Journal of General Medicine (2026)

Yaling Li, Xiuhong Yang, Shuli Hu Department of Intensive Care Unit, Wuhan No. 1 Hospital, Wuhan, 430022, People’s Republic of ChinaCorrespondence: Shuli Hu, Department of Intensive Care Unit, Wuhan No. 1 Hospital, No. 215 Zhongshan Avenue,...

DOAJ Open Access (DOAJ)

Epistemic frontiers and the distinction between causality, information, and predictability in pattern recognition

Pablo Neirz, Héctor Allende, Carolina Saavedra • Scientific Reports (2026)

Abstract High predictive accuracy is frequently misinterpreted as evidence of causal understanding or population-level signal. Models can exploit spurious correlations, confounding, or protocol-induced artefacts, while post-hoc explanations...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-52883-z

A review of machine learning in obesity

K. W. DeGregory, Patrick K. Kuiper, Thomas DeSilvio, James D. Pleuss et al. • Obesity Reviews (2018)

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...

OPENALEX Open Access DOI: https://doi.org/10.1111/obr.12667 PMC: 8176949

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

Machine Learning for Stock Selection

Keywan Christian Rasekhschaffe, Robert C. Jones • Financial Analysts Journal (2019)

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can un...

OPENALEX DOI: https://doi.org/10.1080/0015198x.2019.1596678

Fatigue Monitoring Through Wearables: A State-of-the-Art Review

Neusa R. Adão Martins, Neusa R. Adão Martins, Simon Annaheim, Christina M. Spengler et al. • Frontiers in Physiology (2021)

The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems...

DOAJ Open Access (DOAJ) DOI: 10.3389/fphys.2021.790292

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas

Shuchen Sun, Shuchen Sun, Shuchen Sun, Leihao Ren et al. • Frontiers in Oncology (2022)

PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...

DOAJ Open Access (DOAJ) DOI: 10.3389/fonc.2022.879528

Integrating InVEST and machine learning to model mangrove habitat degradation trend in in Northern Persian Gulf, Iran

Mohamad Kazemi, Atefeh Jafarpoor, Youssef Ahmadi, Raoof Mostafazadeh • Scientific Reports (2026)

Abstract The expansion of human activities and environmental changes in coastal desert and semi-desert ecosystems significantly impact habitat quality. This study used remote sensing data on the Google Earth Engine (GEE) platform to generat...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-47305-z

An ensemble approach for imbalanced multiclass malware classification using 1D-CNN

Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science (2023)

Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1677

Acceptance of Machine Learning for Medication Selection in Epilepsy to Inform Clinical Trial Design: Co-Design Survey Study

Madeleine J Smith, Sandra Reeder, Fiona Waugh, Shobi Sivathamboo et al. • JMIR AI (2026)

Abstract BackgroundAntiseizure medications (ASMs) are the mainstay of epilepsy treatment; however, there is currently no reliable way to predict which medication will be most effective for an individual patient. Machine learning...

DOAJ Open Access (DOAJ) DOI: 10.2196/85047

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

Empirical Asset Pricing via Machine Learning

Shihao Gu, Bryan Kelly, Dacheng Xiu • Review of Financial Studies (2020)

Abstract We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, i...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1093/rfs/hhaa009