[HTML][HTML] Artificial intelligence and obesity management: an obesity medicine association (OMA) clinical practice statement (CPS) 2023
HE Bays, A Fitch, S Cuda, S Gonsahn-Bollie, E Rickey… - Obesity Pillars, 2023 - Elsevier
Abstract Background This Obesity Medicine Association (OMA) Clinical Practice Statement
(CPS) provides clinicians an overview of Artificial Intelligence, focused on the management …
(CPS) provides clinicians an overview of Artificial Intelligence, focused on the management …
[HTML][HTML] Obesity, diabetes mellitus, and cardiometabolic risk: an obesity medicine association (OMA) clinical practice statement (CPS) 2023
HE Bays, S Bindlish, TL Clayton - Obesity Pillars, 2023 - Elsevier
Abstract Background This Obesity Medicine Association (OMA) Clinical Practice Statement
(CPS) is intended to provide clinicians an overview of type 2 diabetes mellitus (T2DM), an …
(CPS) is intended to provide clinicians an overview of type 2 diabetes mellitus (T2DM), an …
[HTML][HTML] Obesity and hypertension: obesity medicine association (OMA) clinical practice statement (CPS) 2023
TL Clayton, A Fitch, HE Bays - Obesity Pillars, 2023 - Elsevier
Abstract Background This Obesity Medicine Association (OMA) Clinical Practice Statement
(CPS) provides an overview of the mechanisms and treatment of obesity and hypertension …
(CPS) provides an overview of the mechanisms and treatment of obesity and hypertension …
[HTML][HTML] Why does type 2 diabetes mellitus impair weight reduction in patients with obesity? A review
HE Bays - Obesity Pillars, 2023 - Elsevier
Background A common adiposopathic complication of obesity is type 2 diabetes mellitus.
Healthful weight reduction in patients with obesity can improve glucose metabolism and …
Healthful weight reduction in patients with obesity can improve glucose metabolism and …
[HTML][HTML] Obesity Pillars Roundtable: Body mass index and body composition in Black and Female individuals. Race-relevant or racist? Sex-relevant or sexist?
HE Bays, S Gonsahn-Bollie, C Younglove, S Wharton - Obesity Pillars, 2022 - Elsevier
Background Body mass index (BMI or weight in kilograms/height in meters 2) is the most
common metric to diagnose overweight and obesity. However, a body composition analysis …
common metric to diagnose overweight and obesity. However, a body composition analysis …
[HTML][HTML] Obesity, thrombosis, venous disease, lymphatic disease, and lipedema: An obesity medicine association (OMA) clinical practice statement (CPS) 2023
S Bindlish, J Ng, W Ghusn, A Fitch, HE Bays - Obesity Pillars, 2023 - Elsevier
Abstract Background This Obesity Medicine Association (OMA) Clinical Practice Statement
(CPS) is intended to provide clinicians with an overview on obesity, thrombosis, venous …
(CPS) is intended to provide clinicians with an overview on obesity, thrombosis, venous …
ANMCO (Italian Association of Hospital Cardiologists) scientific statement: obesity in adults—an approach for cardiologists
SA Di Fusco, E Mocini, MM Gulizia, D Gabrielli… - Eating and Weight …, 2024 - Springer
Obesity is a complex, chronic disease requiring a multidisciplinary approach to its
management. In clinical practice, body mass index and waist-related measurements can be …
management. In clinical practice, body mass index and waist-related measurements can be …
[HTML][HTML] Atherosclerotic plaque in individuals without known cardiovascular disease but with established obstructive sleep apnea and at high risk of obstructive sleep …
Objectives In a large US cohort free of CVD evaluated by coronary computed CT
angiography, we aimed to assess the association between established/high risk of …
angiography, we aimed to assess the association between established/high risk of …
Social media for obesity education: a general overview for the novice creator
SI Sobel, JJ Dube - Advances in Physiology Education, 2024 - journals.physiology.org
Rates of obesity continue to rise in the United States and across the globe. Obesity is a risk
factor for developing insulin resistance, type 2 diabetes, and cardiovascular disease. For …
factor for developing insulin resistance, type 2 diabetes, and cardiovascular disease. For …
Machine-Learning-Based-Approaches for Sleep Stage Classification Utilising a Combination of Physiological Signals: A Systematic Review
Increasingly prevalent sleep disorders worldwide significantly affect the well-being of
individuals. Sleep disorder can be detected by dividing sleep into different stages. Hence …
individuals. Sleep disorder can be detected by dividing sleep into different stages. Hence …