Endocrinology and Metabolism

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Identification of Healthy and Unhealthy Lifestyles by a Wearable Activity Tracker in Type 2 Diabetes: A Machine Learning-Based Analysis

Kyoung Jin Kim, Jung-Been Lee, Jimi Choi, Ju Yeon Seo, Ji Won Yeom, Chul-Hyun Cho, Jae Hyun Bae, Sin Gon Kim, Heon-Jeong Lee, Nam Hoon Kim

Endocrinol Metab. 2022;37(3):547-551. Published online June 29, 2022
DOI: https://doi.org/10.3803/EnM.2022.1479

Identification of Healthy and Unhealthy Lifestyles by a Wearable Activity Tracker in Type 2 Diabetes: A Machine Learning-Based Analysis

Kyoung Jin Kim, Jung-Been Lee, Jimi Choi, Ju Yeon Seo, Ji Won Yeom, Chul-Hyun Cho, Jae Hyun Bae, Sin Gon Kim, Heon-Jeong Lee, Nam Hoon Kim

Endocrinology and Metabolism. 2022;37(3):547-551

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Activity Identification using Supervised Machine Learning on Wearable Activity Tracker Data

Sejal Bhatia

2021 Asian Conference on Innovation in Technology (ASIANCON). 2021;

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Healthy lifestyles in Europe: prevention of obesity and type II diabetes by diet and physical activity

Arne Astrup

Public Health Nutrition. 2001;4(2b):499-515

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Wearable Physical Activity and Sleep Tracker Based Healthy Lifestyle Intervention in Early Intervention Psychosis (EIP) Service: Patient Experiences

Chris Griffiths, Kate Walker, Chloe Leathlean

Open Journal of Psychiatry. 2022;12(01):115-127

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Activity tracker-based intervention to increase physical activity in patients with type 2 diabetes and healthy individuals: study protocol for a randomized controlled trial

Mareike Mähs, Jana Sabrina Pithan, Isabell Bergmann, Lars Gabrys, Jonathan Graf, Alexander Hölzemann, Kristof Van Laerhoven, Silke Otto-Hagemann, Maria Loredana Popescu, Lisa Schwermann, Benjamin Wenz, Iris Pahmeier, Andrea Teti

. 2022;

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A Comparative Analysis of Ensemble Based Machine Learning Techniques for Diabetes Identification

Nahid Hossain Taz, Abrar Islam, Ishrak Mahmud

2021 2nd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST). 2021;

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Masking technique based attention mechanism for off-type identification in plants

G. Jaya Brindha, E.S. Gopi

Machine Learning with Applications. 2022;8:100282

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Identification of Prevotella, Anaerotruncus and Eubacterium Genera by Machine Learning Analysis of Metagenomic Profiles for Stratification of Patients Affected by Type I Diabetes

Diego Fernández-Edreira, Jose Liñares-Blanco, Carlos Fernandez-Lozano

3rd XoveTIC Conference. 2020;

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IDF21-0488 A comparison of healthy lifestyles between pregnant women with gestational diabetes and pre-existing type 2 diabetes

R. Staynova, T. Stankova, V. Yanachkova, G. Delcheva

Diabetes Research and Clinical Practice. 2022;186:109554

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The Machine Learning Models for Activity Recognition Applications with Wearable Sensors

Igor Khokhlov, Leon Reznik, Rohit Bhaskar

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). 2019;

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