AIMC Topic: Obesity
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Non-invasive assessment of NAFLD as systemic disease-A machine learning perspective.
PloS one
Mar 26, 2019
BACKGROUND & AIMS: Current non-invasive scores for the assessment of severity of non-alcoholic fatty liver disease (NAFLD) and identification of patients with non-alcoholic steatohepatitis (NASH) have insufficient performance to be included in clinic...
MetaPheno: A critical evaluation of deep learning and machine learning in metagenome-based disease prediction.
Methods (San Diego, Calif.)
Mar 16, 2019
The human microbiome plays a number of critical roles, impacting almost every aspect of human health and well-being. Conditions in the microbiome have been linked to a number of significant diseases. Additionally, revolutions in sequencing technology...
Exploring the interactions between serum free fatty acids and fecal microbiota in obesity through a machine learning algorithm.
Food research international (Ottawa, Ont.)
Dec 5, 2018
Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of body fat storage, and a link between diet, FFA and the intestinal microbiota seems to exist. Our ai...
Insulin resistance and adrenal incidentalomas: A bidirectional relationship.
Maturitas
Dec 5, 2018
An adrenal incidentaloma (AI) is an adrenal mass incidentally found via a radiological modality, independent of an endocrinological investigation. In this review, we aimed to investigate the possible reasons behind the increased frequency in AI detec...
Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?
Journal of behavioral medicine
Aug 25, 2018
Behavioral weight loss (WL) trials show that, on average, participants regain lost weight unless provided long-term, intensive-and thus costly-intervention. Optimization solutions have shown mixed success. The artificial intelligence principle of "re...
Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.
JAMA network open
Aug 3, 2018
IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has been linked to factors such as genetics, diet, physical activity, and the environment. However, evidence indicating associations between the built envi...
OC-2-KB: integrating crowdsourcing into an obesity and cancer knowledge base curation system.
BMC medical informatics and decision making
Jul 23, 2018
BACKGROUND: There is strong scientific evidence linking obesity and overweight to the risk of various cancers and to cancer survivorship. Nevertheless, the existing online information about the relationship between obesity and cancer is poorly organi...
Application of Machine Learning to Predict Dietary Lapses During Weight Loss.
Journal of diabetes science and technology
May 24, 2018
BACKGROUND: Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of resea...
A review of machine learning in obesity.
Obesity reviews : an official journal of the International Association for the Study of Obesity
Feb 9, 2018
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning prov...
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