Deep learning for diabetes: a systematic review

T Zhu, K Li, P Herrero… - IEEE Journal of Biomedical …, 2020 - ieeexplore.ieee.org
Diabetes is a chronic metabolic disorder that affects an estimated 463 million people
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …

[HTML][HTML] Mapping the evidence on the effectiveness of telemedicine interventions in diabetes, dyslipidemia, and hypertension: an umbrella review of systematic …

P Timpel, S Oswald, PEH Schwarz, L Harst - Journal of medical Internet …, 2020 - jmir.org
Background Telemedicine is defined by three characteristics:(1) using information and
communication technologies,(2) covering a geographical distance, and (3) involving …

Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective

Y Zou, Z Chu, J Guo, S Liu, X Ma, J Guo - Biosensors and Bioelectronics, 2023 - Elsevier
Diabetes and its complications are seriously threatening the health and well-being of
hundreds of millions of people. Glucose levels are essential indicators of the health …

Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients

Y Deng, L Lu, L Aponte, AM Angelidi, V Novak… - NPJ Digital …, 2021 - nature.com
Accurate prediction of blood glucose variations in type 2 diabetes (T2D) will facilitate better
glycemic control and decrease the occurrence of hypoglycemic episodes as well as the …

Exploring the intersection of artificial intelligence and clinical healthcare: a multidisciplinary review

CS Stafie, IG Sufaru, CM Ghiciuc, II Stafie, EC Sufaru… - Diagnostics, 2023 - mdpi.com
Artificial intelligence (AI) plays a more and more important role in our everyday life due to the
advantages that it brings when used, such as 24/7 availability, a very low percentage of …

Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review

E Afsaneh, A Sharifdini, H Ghazzaghi… - Diabetology & Metabolic …, 2022 - Springer
Diabetes as a metabolic illness can be characterized by increased amounts of blood
glucose. This abnormal increase can lead to critical detriment to the other organs such as …

[HTML][HTML] Deep learning in mHealth for cardiovascular disease, diabetes, and cancer: systematic review

A Triantafyllidis, H Kondylakis, D Katehakis… - JMIR mHealth and …, 2022 - mhealth.jmir.org
Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and
cancer impose a significant burden on people and health care systems around the globe …

Sense and learn: recent advances in wearable sensing and machine learning for blood glucose monitoring and trend-detection

AY Alhaddad, H Aly, H Gad, A Al-Ali… - … in Bioengineering and …, 2022 - frontiersin.org
Diabetes mellitus is characterized by elevated blood glucose levels, however patients with
diabetes may also develop hypoglycemia due to treatment. There is an increasing demand …

Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study

WPTM van Doorn, YD Foreman, NC Schaper… - PloS one, 2021 - journals.plos.org
Background Closed-loop insulin delivery systems, which integrate continuous glucose
monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown …

[HTML][HTML] Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: a systematic review and meta-analysis

S Lee, Y Chu, J Ryu, YJ Park, S Yang… - Yonsei medical …, 2022 - ncbi.nlm.nih.gov
Purpose Several artificial intelligence (AI) models for the detection and prediction of
cardiovascular-related diseases, including arrhythmias, diabetes, and sleep apnea, have …