Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Malinda Peeples"'
Autor:
Mansur Shomali, Pablo Mora, Grazia Aleppo, Malinda Peeples, Abhimanyu Kumbara, Janice MacLeod, Anand Iyer
Publikováno v:
Frontiers in Endocrinology, Vol 15 (2024)
Digital innovations provide novel opportunities to individualize a person’s care to best match their lifestyle needs and circumstances and to support them as they live their daily lives with diabetes. These innovations also serve to provide actiona
Externí odkaz:
https://doaj.org/article/d406c171d81544769d5321fc6501bc63
Autor:
Vanessa D. Colicchio, Julia E. Blanchette, Deborah A Greenwood, Kirsten Yehl, Malinda Peeples, Jane K. Dickinson, Andrew Todd, Allyson Hughes, Jiancheng Ye, Diana Isaacs, Michelle L. Litchman
Publikováno v:
J Diabetes Sci Technol
Background: A 2017 umbrella review defined the technology-enabled self-management (TES) feedback loop associated with a significant reduction in A1C. The purpose of this 2021 review was to develop a taxonomy of intervention attributes in technology-e
Autor:
Michelle Dugas, Mansur Shomali, Weiguang Wang, Guodong Gordon Gao, Anand K. Iyer, Kenyon Crowley, Malinda Peeples
Publikováno v:
J Diabetes Sci Technol
Background: Digital health solutions targeting diabetes self-care are popular and promising, but important questions remain about how these tools can most effectively help patients. Consistent with evidence of the salutary effects of note-taking in e
Autor:
Diana Isaacs, Gretchen Yousef, Kirsten Yehl, LaurieAnn Scher, Malinda Peeples, Deborah A Greenwood, Joanne Rinker, Fran Howell
Publikováno v:
The Diabetes Educator. 46:315-322
PurposeThe purpose of this article is to present a framework for optimizing technology-enabled diabetes and cardiometabolic care and education using a standardized approach. This approach leverages the expertise of the diabetes care and education spe
Publikováno v:
Health Informatics ISBN: 9783031079115
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47493308e9b880666bfaf513d539b42c
https://doi.org/10.1007/978-3-031-07912-2_14
https://doi.org/10.1007/978-3-031-07912-2_14
Autor:
Abhimanyu Kumbara, Michelle Dugas, Shiping Liu, Kenyon Crowley, Mansur Shomali, Malinda Peeples, Guodong Gao, Anand K. Iyer
Publikováno v:
Diabetes. 70
Introduction: Many CGM users find the magnitude and complexity of their data challenging. We developed an AI method for detecting and classifying discernable self-management events reflected in CGM data. Methods: Machine learning and signal detection
Autor:
Mansur Shomali, Shiping Liu, Michelle Dugas, Kenyon Crowley, Abhimanyu Kumbara, Malinda Peeples, Guodong Gao, Anand K. Iyer
Publikováno v:
Diabetes. 70
Introduction: The Ambulatory Glucose Profile (AGP) visualizes and summarizes complex CGM data and contains multiple and often difficult to interpret measures. Our objective was to create a simple visual summary of the data that can provide insights f
Autor:
Anand K. Iyer, Malinda Peeples
Publikováno v:
Mhealth Innovation ISBN: 9781003192893
Mhealth Innovation
Mhealth Innovation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f087afe7f05344517da847811a1fcf4f
https://doi.org/10.4324/9781003192893-18
https://doi.org/10.4324/9781003192893-18
Publikováno v:
J Diabetes Sci Technol
Autor:
Janice Macleod, Malinda Peeples
Publikováno v:
AADE in Practice. 5:30-35