Journal List > J Korean Diabetes > v.18(1) > 1055052

Cho: The Role of a Diabetologist in the New Era of Artificial Intelligence

Abstract

Artificial intelligence is expected to be applied to various fields in industry and is also introducing a new era in the field of medicine. Artificial intelligence, which is called machine learning or deep learning, analyzes big data, identifies patterns, and performs a task according to an analysis result or pattern. In the medical field, artificial intelligence could be used for such things as disease diagnosis, prediction of complications, or correction of user behavior using big digital data collected from many sources and populations across the world. For diabetes, various studies to predict glycemic response or diabetic complications or to calculate insulin dose are being carried out. In the new era of artificial intelligence, diabetologists need to use the new system to obtain information more actively, explain it to patients in more detail, and support them based on evidence and data.

References

1. Kwon HS, Cho JH, Kim HS, Song BR, Ko SH, Lee JM, Kim SR, Chang SA, Kim HS, Cha BY, Lee KW, Son HY, Lee JH, Lee WC, Yoon KH. Establishment of blood glucose monitoring system using the internet. Diabetes Care. 2004; 27:478–83.
crossref
2. Wang G, Zhang Z, Feng Y, Sun L, Xiao X, Wang G, Gao Y, Wang H, Zhang H, Deng Y, Sun C. Telemedicine in the management of type 2 diabetes mellitus. Am J Med Sci. 2017; 353:1–5.
crossref
3. Cho JH, Kim HS, Yoo SH, Jung CH, Lee WJ, Park CY, Yang HK, Park JY, Park SW, Yoon KH. An internet-based health gateway device for interactive communication and automatic data uploading: clinical efficacy for type 2 diabetes in a multicentre trial. J Telemed Telecare 2016. doi: 10.1177/1357633X16657500. [Epub ahead of print].
4. Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalová L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized nutrition by prediction of glycemic responses. Cell. 2015; 163:1079–94.
crossref
5. Artificial Intelligence for Diabetes. 1st ECAI Workshop on Artificial intelligence for Diabetes at the 22nd European Conference on Artificial Intelligence (ECAI 2016);. 2016. Aug 30; Hague, Holland. Artificial Intelligence for Diabetes; 2016. 42 p.
6. Herrero P, López B, Martin C. PEPPER: patient empowerment through predictive personalised decision support. Paper presented at: Artificial Intelligence for Diabetes 1st ECAI Workshop on Artificial intelligence for Diabetes at the 22nd European Conference on Artificial Intelligence (ECAI 2016);. 2016. Aug 30; Hague, Holland. p.8–9.
7. Cvetković B, Pangerc U, Gradišek A, Luštrek M. Monitoring patients with diabetes using wearable sensors: predicting glycaemias using ECG and respiration rate. Paper presented at: Artificial Intelligence for Diabetes 1st ECAI Workshop on Artificial intelligence for Diabetes at the 22nd European Conference on Artificial Intelligence (ECAI 2016);. 2016. Aug 30; Hague, Holland. p.18–21.
8. Armengol E. Assessment of diabetic complications based on series of records. Paper presented at: Artificial Intelligence for Diabetes 1st ECAI Workshop on Artificial intelligence for Diabetes at the 22nd European Conference on Artificial Intelligence (ECAI 2016);. 2016. Aug 30; Hague, Holland. p.28–30.
TOOLS
Similar articles