Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors

Vettoretti, Martina; Cappon, Giacomo; Facchinetti, Andrea; Sparacino, Giovanni

doi:10.3390/s20143870

Cited by 80 publications

(43 citation statements)

References 61 publications

(86 reference statements)

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“…Tyler and Jacobs [ 164 ] explore into DSS, focusing on ready-to-use tools and systems in clinical studies (some in silico, some in vivo). Vettoretti et al [ 165 ] evaluate DSS provided by continuous glucose monitoring (CGM) data and AI techniques for T1DM. CGM readings have also enabled the development of AID systems, which employ CGM measures to regulate insulin supply via an insulin pump.…”

Section: Ai In the Management Of Diabetesmentioning

confidence: 99%

Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents

Alqahtani

2022

Evidence-Based Complementary and Alternative Medicine

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Spectacular developments in molecular and cellular biology have led to important discoveries in cancer research. Despite cancer is one of the major causes of morbidity and mortality globally, diabetes is one of the most leading sources of group of disorders. Artificial intelligence (AI) has been considered the fourth industrial revolution machine. The most major hurdles in drug discovery and development are the time and expenditures required to sustain the drug research pipeline. Large amounts of data can be explored and generated by AI, which can then be converted into useful knowledge. Because of this, the world’s largest drug companies have already begun to use AI in their drug development research. In the present era, AI has a huge amount of potential for the rapid discovery and development of new anticancer drugs. Clinical studies, electronic medical records, high-resolution medical imaging, and genomic assessments are just a few of the tools that could aid drug development. Large data sets are available to researchers in the pharmaceutical and medical fields, which can be analyzed by advanced AI systems. This review looked at how computational biology and AI technologies may be utilized in cancer precision drug development by combining knowledge of cancer medicines, drug resistance, and structural biology. This review also highlighted a realistic assessment of the potential for AI in understanding and managing diabetes.

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Section: Ai In the Management Of Diabetesmentioning

confidence: 99%

Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents

Alqahtani

2022

Evidence-Based Complementary and Alternative Medicine

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“…Although severe hypoglycemic episodes can be reduced by using RT-CGM, it may not improve glycemic control (time above range or time in range) compared with intensive insulin therapy following the guidance of an algorithm[ 14 , 16 , 17 ]. Additionally, artificial intelligence can analyze the glucose level readings, medications and food automatically and predict mortality[ 18 ]. Recently, many closed-loop systems of integrated CGM and automated insulin delivery have been investigated and approved for specific groups of people[ 19 ].…”

Section: Cons Of Cgm In the Icumentioning

confidence: 99%

Pros and cons of continuous glucose monitoring in the intensive care unit

Sun¹,

Li²,

Lin³

et al. 2021

WJCC

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Diabetes mellitus affects people worldwide, and management of its acute complications or treatment-related adverse events is particularly important in critically ill patients. Previous reports have confirmed that hyperglycemia can increase the risk of mortality in patients cared in the intensive care unit (ICU). In addition, severe and multiple hypoglycemia increases the risk of mortality when using insulin or intensive antidiabetic therapy. The innovation of continuous glucose monitoring (CGM) may help to alert medical caregivers with regard to the development of hyperglycemia and hypoglycemia, which may decrease the potential complications in patients in the ICU. The major limitation of CGM is the measurement of interstitial glucose levels rather than real-time blood glucose levels; thus, there will be a delay in the treatment of hyperglycemia and hypoglycemia in patients. Recently, the European Union approved a state-of-art artificial intelligence directed loop system coordinated by CGM and a continuous insulin pump for diabetes control, which may provide a practical way to prevent acute adverse glycemic events related to antidiabetic therapy in critically ill patients. In this mini-review paper, we describe the application of CGM to patients in the ICU and summarize the pros and cons of CGM.

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“…Иногда применяется сравнение этих значений с показателями лиц без СД [8]. Наиболее значимые параметры гликемического контроля, применяемые в компьютерном и мобильном ПО, [44][45][46].…”

Section: методы исследования вариабельности гликемии используемые в компьютерных программах и мобильных приложенияхunclassified

Computer Software and Mobile Applications for Glycemic Variability Assessment: Current Developments and Outlook

Rusanov¹,

Rodionova²

2021

СПНО (MPSE)

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Современные информационные технологии открывают новые возможности в управлении сахарным диабетом. Компьютерные программы и мобильные приложения активно используются для исследования вариабельности глюкозы -одного из значимых показателей гликемического контроля. Цель настоящего обзора: провести анализ актуальной литературы о программном обеспечении для оценки вариабельности гликемии. Поиск литературных источников проводился с использованием баз данных PubMed, Google Scholar, E-library. На основании выявленной информации были подтверждены актуальность проблемы, необходимость дальнейшего развития компьютерных программ и мобильных приложений для управления сахарным диабетом. Была отмечена роль программ для персонального компьютера в профессиональной оценке вариабельности гликемии. Доступные в настоящее время мобильные приложения в большей степени ориентированы на применение пациентом с целью самоконтроля. Наиболее активно развивающаяся категория мобильного программного обеспечения для мониторинга глюкозы требует дальнейших исследований эффективности и безопасности применения в клинической практике, имеет существенные ограничения для объективной оценки вариабельности гликемии. Компьютерные программы и мобильные приложения -перспективное средство, которое обладает потенциалом для выявления и коррекции повышенной вариабельности гликемии у пациентов с сахарным диабетом. Ключевые слова: вариабельность гликемии, компьютерные программы, мобильные приложения, непрерывный мониторинг глюкозы, самостоятельный мониторинг глюкозы крови.

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Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors

Cited by 80 publications

References 61 publications

Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents

Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents

Pros and cons of continuous glucose monitoring in the intensive care unit

Computer Software and Mobile Applications for Glycemic Variability Assessment: Current Developments and Outlook

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