Cargando…
SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus
Background: Diet control is the basis of the treatment of type 2 diabetes. However, the education and practice of diet control for the patients with type 2 diabetes mellitus (T2DM) need a lot of manpower and time. In 2009, we have developed a telemedicine model that nutritionists analyze photos of T...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7209668/ http://dx.doi.org/10.1210/jendso/bvaa046.2214 |
_version_ | 1783531132065677312 |
---|---|
author | Higashitani, Takuya Kometani, Mitsuhiro Oka, Rie Gondo, Yuko Nomura, Akihiro Yasugi, Ayaka Aono, Daisuke Karashima, Shigehiro Yoneda, Takashi |
author_facet | Higashitani, Takuya Kometani, Mitsuhiro Oka, Rie Gondo, Yuko Nomura, Akihiro Yasugi, Ayaka Aono, Daisuke Karashima, Shigehiro Yoneda, Takashi |
author_sort | Higashitani, Takuya |
collection | PubMed |
description | Background: Diet control is the basis of the treatment of type 2 diabetes. However, the education and practice of diet control for the patients with type 2 diabetes mellitus (T2DM) need a lot of manpower and time. In 2009, we have developed a telemedicine model that nutritionists analyze photos of T2DM patients’ meal and supervise them remotely. Our system resulted in the improvement of glycemic control of T2DM patients. Recently, the image analysis technology using the artificial intelligence (AI) progresses rapidly. The smart device application “Asken” has an AI-powered photo analysis system which analyzes the photo of the entire meal and identifies the frame of each item as well as its menu and serving amount. In addition, this application delivers individualized dietary messages and feedbacks. Case reports: We report two T2DM cases who conducted nutrient intervention by this application. One case was a 72-year-old man whose HbA1c decreased from 7.2% to 6.6% and weighed from 58.7kg to 57.5kg in 4 months. However, his total cholesterol increased from 119mg/dl to 200mg/dl, and low-density lipoprotein cholesterol (LDL) also increased from 47mg/dl to 106mg/dl. Another case is a 60-year-old man whose HbA1c improved from 7.0% to 6.6% and his weight decreased from 78.0kg to 76.0kg in 3 months. Total cholesterol was 140mg/dl to 128mg/dl, and LDL-cholesterol was from 65mg/dl to 54mg/dl. Conclusion: Using this application might be useful for diet control of T2DM patients. The effects of AI-supported nutrient intervention using application like this should be further clarified in the large number of patients. |
format | Online Article Text |
id | pubmed-7209668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-72096682020-05-13 SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus Higashitani, Takuya Kometani, Mitsuhiro Oka, Rie Gondo, Yuko Nomura, Akihiro Yasugi, Ayaka Aono, Daisuke Karashima, Shigehiro Yoneda, Takashi J Endocr Soc Diabetes Mellitus and Glucose Metabolism Background: Diet control is the basis of the treatment of type 2 diabetes. However, the education and practice of diet control for the patients with type 2 diabetes mellitus (T2DM) need a lot of manpower and time. In 2009, we have developed a telemedicine model that nutritionists analyze photos of T2DM patients’ meal and supervise them remotely. Our system resulted in the improvement of glycemic control of T2DM patients. Recently, the image analysis technology using the artificial intelligence (AI) progresses rapidly. The smart device application “Asken” has an AI-powered photo analysis system which analyzes the photo of the entire meal and identifies the frame of each item as well as its menu and serving amount. In addition, this application delivers individualized dietary messages and feedbacks. Case reports: We report two T2DM cases who conducted nutrient intervention by this application. One case was a 72-year-old man whose HbA1c decreased from 7.2% to 6.6% and weighed from 58.7kg to 57.5kg in 4 months. However, his total cholesterol increased from 119mg/dl to 200mg/dl, and low-density lipoprotein cholesterol (LDL) also increased from 47mg/dl to 106mg/dl. Another case is a 60-year-old man whose HbA1c improved from 7.0% to 6.6% and his weight decreased from 78.0kg to 76.0kg in 3 months. Total cholesterol was 140mg/dl to 128mg/dl, and LDL-cholesterol was from 65mg/dl to 54mg/dl. Conclusion: Using this application might be useful for diet control of T2DM patients. The effects of AI-supported nutrient intervention using application like this should be further clarified in the large number of patients. Oxford University Press 2020-05-08 /pmc/articles/PMC7209668/ http://dx.doi.org/10.1210/jendso/bvaa046.2214 Text en © Endocrine Society 2020. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Diabetes Mellitus and Glucose Metabolism Higashitani, Takuya Kometani, Mitsuhiro Oka, Rie Gondo, Yuko Nomura, Akihiro Yasugi, Ayaka Aono, Daisuke Karashima, Shigehiro Yoneda, Takashi SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title | SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title_full | SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title_fullStr | SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title_full_unstemmed | SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title_short | SUN-LB110 The Nutrition Education Using a Health Care Application With Artificial Intelligence in Patients With Diabetes Mellitus |
title_sort | sun-lb110 the nutrition education using a health care application with artificial intelligence in patients with diabetes mellitus |
topic | Diabetes Mellitus and Glucose Metabolism |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7209668/ http://dx.doi.org/10.1210/jendso/bvaa046.2214 |
work_keys_str_mv | AT higashitanitakuya sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT kometanimitsuhiro sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT okarie sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT gondoyuko sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT nomuraakihiro sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT yasugiayaka sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT aonodaisuke sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT karashimashigehiro sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus AT yonedatakashi sunlb110thenutritioneducationusingahealthcareapplicationwithartificialintelligenceinpatientswithdiabetesmellitus |