Assessing the Impact of Artificial Intelligence Applications on Diagnostic Accuracy in Saudi Arabian Healthcare: A Systematic Review

The Open Public Health Journal, Journal Year: 2025, Volume and Issue: 18(1)

Published: Feb. 7, 2025

Background Artificial intelligence (AI) has become a disruptive force with great potential to revolutionize healthcare. The integration of artificial in healthcare practices and its use areas, such as the detection diagnosis diseases, led an increased interest this topic, which been key informing research study determine effect on diagnostic accuracy. However, impact AI accuracy, particularly context Saudi Arabia, remains underexplored area research. Aim This systematic review sought address gap by analyzing applications' accuracy Arabia's Methods employed structured search strategy compliance Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) criteria. Three databases were used identify articles, including PubMed, Embase, CINAHL. relevant articles linked applications KSA sector was narrowed down published between 2013 2023. step generated 450 further evaluated based inclusion criteria narrow 12 analysis. Results 11 out studies conducted 2020 2023, indicating that last three years have witnessed largest number intelligence. included within different hospitals. 7 cross-sectional studies, 3 observational (1 retrospective study), 1 experimental study, randomized controlled trial (RCT). They all showed increasing healthcare, is enhancing overall outcomes helpful wide variety diseases conditions, chronic diseases. Conclusion models shown capable diagnostics treatment quality, can be essential planning preventing care line Vision 2030. Hence, findings contribute better understanding role offer insights applicable regions facing similar challenges. PROSPERO Registration Number 611347

Language: Английский

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Optimal Convolutional Networks for Staging and Detecting of Diabetic Retinopathy

Information, Journal Year: 2025, Volume and Issue: 16(3), P. 221 - 221

Published: March 13, 2025

Diabetic retinopathy (DR) is the main ocular complication of diabetes. Asymptomatic for a long time, it subject to annual screening using dilated fundus or retinal photography look early signs. Fundus and optical coherence tomography (OCT) are used by ophthalmologists assess thickness structure, as well detect edema, hemorrhage, scarring. The effectiveness ConvNet no longer needs be demonstrated, its use in field imaging has made possible overcome many barriers, which were until now insurmountable with old methods. Throughout this study, robust optimal deep proposed analyze images automatically distinguish between healthy, moderate, severe DR. model combines architecture taken from ImageNet, data augmentation, class balancing, transfer learning order establish benchmarking test. A significant improvement at level middle corresponds stage DR, was major problem previous studies. By eliminating need retina specialists broadening access care, substantially more objectively staging detecting

Language: Английский

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Artificial Intelligence in Healthcare: A Study of Physician Attitudes and Perceptions in Jeddah, Saudi Arabia

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: March 30, 2024

Background Artificial intelligence (AI) in healthcare is rapidly advancing, reshaping diagnostic, prognostic, and operational tasks institutions. The adoption of AI among physicians varied, with concerns over job loss, medical errors, lack emotional intelligence. This study aimed to assess physicians' attitudes perceptions toward clinical practice Jeddah, Saudi Arabia, the factors affecting these perceptions. Methodology A cross-sectional was conducted at two major hospitals Jeddah. An in-person digital survey consisted questions regarding demographic characteristics, AI, AI's impact on healthcare. Results Of 205 participants, 76% agreed accuracy systems, 60% acknowledged their efficiency as a factor that could influence willingness use AI. However, only 25.9% reported using systems past year, majority, 74.1%, indicating they had never used them. Notably, there significant association between gender attitude males being more likely have positive (p = 0.01). Conclusions While majority participants recognized potential benefits healthcare, its actual utilization low. findings suggest need for increased AI-related training education fostering collaboration computer scientists, engineers, professionals accelerate development clinically relevant tools.

Language: Английский

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Detection of diabetic retinopathy using artificial intelligence: an exploratory systematic review

LatIA, Journal Year: 2024, Volume and Issue: 2, P. 112 - 112

Published: Sept. 2, 2024

Diabetic retinopathy is a disease that can lead to vision loss and blindness in people with diabetes, so its early detection important prevent ocular complications. The aim of this study was analyze the usefulness artificial intelligence diabetic retinopathy. For purpose, an exploratory systematic review performed, collecting 77 empirical articles from Scopus, IEEE, ACM, SciELO NIH databases. results indicate most commonly used factors for include changes retinal vascularization, macular edema microaneurysms. Among applied algorithms are ResNet 101, CNN IDx-DR. In addition, some models reported have accuracy ranging 90% 95%, although accuracies below 80% also been identified. It concluded intelligence, particular deep learning, has shown be effective retinopathy, facilitating timely treatment improving clinical outcomes. However, ethical legal concerns arise, such as privacy security patient data, liability case diagnostic errors, algorithmic bias, informed consent, transparency use intelligence.

Language: Английский

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Awareness, Knowledge, Attitudes, and Practices Regarding Diabetic Retinopathy Among Residents of Jazan City, Saudi Arabia

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 10, 2024

Eye diseases, particularly diabetic retinopathy, cataracts, and glaucoma, are significant public health challenges globally, affecting quality of life. Diabetic a common diabetes complication, is leading cause visual impairment among working-age adults due to chronic hyperglycemia. Despite treatment advances, awareness this condition remains low, especially in high-risk populations. This study explores the awareness, knowledge, attitudes, practices regarding eye residents Jazan City, Saudi Arabia.

Language: Английский

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