Response to Comment on Hásková et al. Real-time CGM Is Superior to Flash Glucose Monitoring for Glucose Control in Type 1 Diabetes: The CORRIDA Randomized Controlled Trial. Diabetes Care 2020;43:2744–2750

Šoupal, Jan; Prázný, Martin

doi:10.2337/dci20-0078

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…The Guardian Connect System (manufactured by Medtronic) is an example of an AI system with this functionality. This system is based on CGM, has an accompanying smartphone application, 144 and was certified by the FDA in 2018. It is characterized by using AI to predict a hypoglycemic attack an hour in advance based on the CGM data and alerts the patient.…”

Section: Conclusion and Perspectivementioning

confidence: 99%

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

Guan,

Li,

Liu

et al. 2023

Cell Reports Medicine

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Section: Conclusion and Perspectivementioning

confidence: 99%

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

Guan,

Li,

Liu

et al. 2023

Cell Reports Medicine

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“…For early intervention, in 2018 the FDA approved the autonomous AI system Digital Diagnostics, which was found to have high diagnostic accuracy in recognizing diabetes retinopathy in retinal screening images 1 . In the same year, the FDA approved the Guardian Connect System, which uses AI technology to interpret biomedical data and predict a hypoglycemic attack an hour in advance 2 . Since then, the FDA has also approved AI technologies that assist with optimizing insulin dosing and therapy for patients 3,4 .…”

mentioning

confidence: 99%

AI-based diabetes care: risk prediction models and implementation concerns

Wang,

Nickel,

Venkatesh

et al. 2024

npj Digit. Med.

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Development of a T2D App for Elderly Users: Participatory Design Study via Heuristic Evaluation and Usability Testing

Liu,

2024

Electronics

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Diabetes management applications effectively help patients monitor blood glucose levels and adjust diet and exercise plans. However, most diabetes management apps, including the SugarShift application developed in 2023, use generalized designs that often fail to consider the unique cognitive and physiological characteristics of elderly users, thereby impacting their acceptance and usage. This paper proposes an enhancement for the SugarShift application by introducing a mode specifically designed for elderly users. This proposed enhancement aims to directly involve elderly patients so as to meet their needs better through a participatory design approach. A heuristic evaluation conducted with six experts identified 126 usability issues and 179 heuristic violations in the current version, which has led to the recommendation to develop optimization strategies tailored for elderly users. Subsequent usability testing with 28 elderly patients and six experts emphasized the importance of interface simplicity, logical operation, and interaction quality in enhancing user experience. These factors improve usability, facilitate information processing, and reduce cognitive load. Despite the overall usability of SUS scores, significant challenges still need to be addressed in information display, system feedback, and user interaction. Recommendations for future enhancements include simplifying data entry and presentation, improving readability, and providing timely feedback to enhance usability and user satisfaction, ultimately increasing user retention.

show abstract

Response to Comment on Hásková et al. Real-time CGM Is Superior to Flash Glucose Monitoring for Glucose Control in Type 1 Diabetes: The CORRIDA Randomized Controlled Trial. Diabetes Care 2020;43:2744–2750

Cited by 3 publications

References 5 publications

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

AI-based diabetes care: risk prediction models and implementation concerns

Development of a T2D App for Elderly Users: Participatory Design Study via Heuristic Evaluation and Usability Testing

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