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Showing 20 of 992 academic articles

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Ferhat Yilmaz, Zeynep Ozguner • Discover Sustainability (2026)

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03275-w

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

Anirban Chaudhuri, Graham Pash, David A. Hormuth, David A. Hormuth et al. • Frontiers in Artificial Intelligence (2023)

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2023.1222612

AI enhanced diagnostic accuracy and workload reduction in hepatocellular carcinoma screening

Rui-Fang Lu, Chao-Yin She, Dan-Ni He, Mei-Qing Cheng et al. • npj Digital Medicine (2025)

Abstract Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies us...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-025-01892-9

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Philipp Fuchs, Ursula Schmidt-Erfurth, Leonard M. Coulibaly, Hrvoje Bogunovic et al. • Scientific Reports (2025)

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-17417-z

Sex-based differences in characteristics, management, and outcomes in heart failure with reduced ejection fraction

Christian Basile, Stefan D. Anker, Gianluigi Savarese • Global Cardiology (2025)

Heart failure with reduced ejection fraction (HFrEF) exhibits significant sex-based differences in clinical presentation, management, and outcomes. This study aimed to evaluate these differences using data from the Swedish Heart Failure Reg...

DOAJ Open Access (DOAJ) DOI: 10.4081/cardio.2025.73

Artificial Intelligence and Surgical Decision-making

Tyler John Loftus, Patrick James Tighe, Amanda C. Filiberto, Philip Alexander Efron et al. • JAMA Surgery (2019)

Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes...

OPENALEX Open Access DOI: https://doi.org/10.1001/jamasurg.2019.4917 PMC: 7286802

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Nodir Rakhimov, Jura Kuvandikov, Ma'ruf Tojiyev, Dilmurod Khasanov et al. • Frontiers in Artificial Intelligence (2026)

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1910842

Artificial intelligence and echocardiography

Maryam Alsharqi, William J. Woodward, J. A. Mumith, D. C. Markham et al. • Echo Research and Practice (2018)

Echocardiography plays a crucial role in the diagnosis and management of cardiovascular disease. However, interpretation remains largely reliant on the subjective expertise of the operator. As a result inter-operator variability and experie...

OPENALEX cc-by DOI: https://doi.org/10.1530/erp-18-0056 PMC: 6280250

Effect of robot-assisted gait training combined with electroacupuncture on lower limb motor function and brain network characteristics in stroke: an EEG study

Haiping Huang, Xinyi Su, Yuqian Zhang, Zhixi Liu et al. • Journal of NeuroEngineering and Rehabilitation (2025)

Abstract Background Stroke survivors often experience residual motor dysfunction in their limbs. Additional physical rehabilitation therapies may further improve patients’ functional outcomes. By combining direct interventions targeting the...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12984-025-01827-1

Achieving health equity through healthcare technology: Perspective from India

Prakamya Gupta, Ranjan Choudhury, Atul Kotwal • Journal of Family Medicine and Primary Care (2023)

India aims to provide universal health coverage to all individuals and communities thus ensuring accessibility, promotive, curative, preventive, rehabilitative, and palliative health services to all. Healthcare technologies play a critical ...

DOAJ Open Access (DOAJ) DOI: 10.4103/jfmpc.jfmpc_321_23

An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients

Faezeh Aghamirzaei, Ahmad Ali Abin, Farzaneh Futuhi • Archives of Academic Emergency Medicine (2025)

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble ma...

DOAJ Open Access (DOAJ) DOI: 10.22037/aaemj.v13i1.2560