Artificial intelligence applied to diabetes complications: a bibliometric analysis

Frontiers in Artificial Intelligence, Год журнала: 2025, Номер 8

Опубликована: Янв. 31, 2025

Artificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis scientific articles field AI complications to explore current research trends cutting-edge hotspots. On April 20, 2024, collected screened relevant published from 1988 2024 PubMed. Based on tools such as CiteSpace, Vosviewer bibliometix, construct knowledge maps visualize literature information, including annual production, authors, countries, institutions, journals, keywords A total 935 meeting criteria were analyzed. The number publications showed an upward trend. Raman, Rajiv most articles, Webster, Dale R had highest collaboration frequency. United States, China, India productive countries. Scientific Reports was journal with publications. three frequent diabetic retinopathy, nephropathy, foot. Machine learning, screening, deep foot are still being researched 2024. Global is expected increase further. investigation retinopathy will be focus future.

Язык: Английский

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Recognizing Human Activities in Ambient Assisted Environment from Wearable Sensor Data Using Gramian Angular Field and Deep CNN

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 199 - 226

Опубликована: Янв. 1, 2025

Язык: Английский

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Enhancing Person-Centric Health Care for Diabetes Prediction: A Comparative Study of LightGBM, XGBoost, and Hybrid LIGB Model

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 127 - 155

Опубликована: Янв. 1, 2025

Язык: Английский

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Optimizing Lung Cancer Prediction Models: A Hybrid Methodology Using GWO and Random Forest

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 59 - 77

Опубликована: Янв. 1, 2025

Язык: Английский

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Empowering early predictions: A paradigm shift in diabetes risk assessment with Deep Active Learning

Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113284 - 113284

Опубликована: Март 1, 2025

Язык: Английский

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Unveiling Explainable AI in Healthcare: Current Trends, Challenges, and Future Directions

Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Год журнала: 2025, Номер 15(2)

Опубликована: Май 11, 2025

ABSTRACT This overview investigates the evolution and current landscape of eXplainable Artificial Intelligence (XAI) in healthcare, highlighting its implications for researchers, technology developers, policymakers. Following PRISMA protocol, we analyzed 89 publications from January 2000 to June 2024, spanning 19 medical domains, with a focus on Neurology Cancer as most studied areas. Various data types are reviewed, including tabular data, imaging, clinical text, offering comprehensive perspective XAI applications. Key findings identify significant gaps, such limited availability public datasets, suboptimal preprocessing techniques, insufficient feature selection engineering, utilization multiple methods. Additionally, lack standardized evaluation metrics practical obstacles integrating systems into workflows emphasized. We provide actionable recommendations, design explainability‐centric models, application diverse methods, fostering interdisciplinary collaboration. These strategies aim guide researchers building robust AI assist developers creating intuitive user‐friendly tools, inform policymakers establishing effective regulations. Addressing these gaps will promote development transparent, reliable, user‐centred ultimately improving decision‐making patient outcomes.

Язык: Английский

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An improved NSGA-II algorithm based on fuzzy logic and learning automata for automatically designing the convolutional neural network for image classification

Multimedia Tools and Applications, Год журнала: 2025, Номер unknown

Опубликована: Май 19, 2025

Язык: Английский

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Identification of sweetpotato virus disease-infected leaves from field images using deep learning

Frontiers in Plant Science, Год журнала: 2024, Номер 15

Опубликована: Ноя. 8, 2024

Sweetpotato virus disease (SPVD) is widespread and causes significant economic losses. Current diagnostic methods are either costly or labor-intensive, limiting both efficiency scalability.

Язык: Английский

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Novel Metaheuristic Algorithms and Their Applications to Efficient Detection of Diabetic Retinopathy

Journal of Artificial Intelligence and Soft Computing Research, Год журнала: 2024, Номер 15(2), С. 167 - 195

Опубликована: Дек. 1, 2024

Abstract It is an extremely important to have AI-based system that can assist specialties correctly identify and diagnosis diabetic retinopathy (DR). In this study, we introduce accurate approach for DR using machine learning (ML) techniques a modified golf optimization algorithm (mGOA). The mGOA optimizes ML classifiers through finding the best available parameters with respect objective functions, hence decreases number of features increases classifier’s accuracy. A fitness function employed minimize feature medical dataset. obtained results showed superiority higher convergence speeds without extra processing costs across datasets compared several competitors. Also, attained maximum accuracy optimally reduced in binary multi-class achieving CEC’2022 benchmark other metaheuristic algorithms. Based on findings, three optimized called mGOA-SVM, mGOA-radial SVM,and mGOA-kNN were introduced as tools classification disease their performance was assessed Messidor EyePACS1 datasets. Experimental demonstrated mGOA-SVM SVM achieved remarkable average 98.5% precision 97.4%.

Язык: Английский

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Artificial Intelligence Enabled Sleep Health Dashboards: Power BI Integration for Data-Driven Lifestyle Modifications

Опубликована: Дек. 18, 2024

Язык: Английский

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