AI telemedicine screening in ophthalmology: health economic considerations

Teo, Zhen Ling; Ting, Daniel Shu Wei

doi:10.1016/s2214-109x(23)00037-2

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…By analysing a vast amount of historical data on maritime health emergencies and safety data, these models can identify potential risks, predict patterns, and provide targeted interventions designed to mitigate them. Third, AI has transformed the field of telemedicine, making it easier for maritime medical professionals to communicate effectively with offshore personnel [45], [46]. This has improved the quality of healthcare available onboard vessels, creating a more connected and responsive maritime medicine system.…”

Section: Discussionmentioning

confidence: 99%

Exploring the integration of artificial intelligence (AI) and augmented reality (AR) in maritime medicine: A narrative literature review (Preprint)

Battineni,

Chintalapudi,

Ricci

et al. 2023

Preprint

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UNSTRUCTURED This narrative literature review explores the integration of artificial intelligence (AI) and augmented reality (AR) in the field of maritime medicine. A comprehensive search was conducted in academic databases using relevant search terms, resulting in the identification of 257 records. After screening for relevance and quality, a final review was conducted on 17 papers. The review highlights the potential applications and benefits of AI and AR in enhancing medical practices and safety measures for seafarers. The integration of AI and AR technologies in maritime medicine shows promise in providing real-time medical assistance, remote consultations, augmented training, and improved diagnostic capabilities. Additionally, AI-driven predictive models can aid in early detection of health issues and support proactive health management onboard ships. Challenges related to data privacy, connectivity at sea, and the need for regulatory frameworks are also discussed. The data analysis reported in this review contributes to a better understanding of the current state and future potential of AI and AR in maritime medicine and provide insights into opportunities for further research and implementation in the maritime industry.

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Section: Discussionmentioning

confidence: 99%

Exploring the integration of artificial intelligence (AI) and augmented reality (AR) in maritime medicine: A narrative literature review (Preprint)

Battineni,

Chintalapudi,

Ricci

et al. 2023

Preprint

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“…The integration of AI into telemedicine, notably its cost-effectiveness and utility in simultaneously screening for multiple eye diseases simultaneously in different settings, underscores its potential to improve patient care [ 26 ]. Moreover, AI predictive analytics can forecast disease progression, paving the way for more tailored prevention strategies and treatment regimens.…”

Section: Introductionmentioning

confidence: 99%

A Beginner’s Guide to Artificial Intelligence for Ophthalmologists

Kang,

Wu,

Yuan

et al. 2024

Ophthalmol Ther

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The integration of artificial intelligence (AI) in ophthalmology has promoted the development of the discipline, offering opportunities for enhancing diagnostic accuracy, patient care, and treatment outcomes. This paper aims to provide a foundational understanding of AI applications in ophthalmology, with a focus on interpreting studies related to AI-driven diagnostics. The core of our discussion is to explore various AI methods, including deep learning (DL) frameworks for detecting and quantifying ophthalmic features in imaging data, as well as using transfer learning for effective model training in limited datasets. The paper highlights the importance of high-quality, diverse datasets for training AI models and the need for transparent reporting of methodologies to ensure reproducibility and reliability in AI studies. Furthermore, we address the clinical implications of AI diagnostics, emphasizing the balance between minimizing false negatives to avoid missed diagnoses and reducing false positives to prevent unnecessary interventions. The paper also discusses the ethical considerations and potential biases in AI models, underscoring the importance of continuous monitoring and improvement of AI systems in clinical settings. In conclusion, this paper serves as a primer for ophthalmologists seeking to understand the basics of AI in their field, guiding them through the critical aspects of interpreting AI studies and the practical considerations for integrating AI into clinical practice.

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“…Due to space limitations, we have not touched the point of the advances and application of artificial intelligence, but we are incredibly happy to share the advances of retinal diseases in this special issue with the readership of the APJO. [5][6][7][8][9]…”

mentioning

confidence: 99%

“…Advances in our understanding is exponentially expanding along with the vast array of treatment options. Due to space limitations, we have not touched the point of the advances and application of artificial intelligence, but we are incredibly happy to share the advances of retinal diseases in this special issue with the readership of the APJO 5–9…”

mentioning

confidence: 99%