AIMC Topic: Anthropometry
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Laboratory parameter-based machine learning model for excluding non-alcoholic fatty liver disease (NAFLD) in the general population.
Alimentary pharmacology & therapeutics
Jun 6, 2017
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 20%-40% of the general population in developed countries and is an increasingly important cause of hepatocellular carcinoma. Electronic medical records facilitate large-scale epidemiologic...
Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine.
PloS one
May 4, 2017
To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in clinical practice. We apply a modern machine learning method, the support vector machine to establish a predicting model for the severity of OSA. The suppor...
Prediction of cold and heat patterns using anthropometric measures based on machine learning.
Chinese journal of integrative medicine
Dec 29, 2016
OBJECTIVE: To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures c...
Phantom Validation of Tc-99m Absolute Quantification in a SPECT/CT Commercial Device.
Computational and mathematical methods in medicine
Dec 14, 2016
. Similar to PET, absolute quantitative imaging is becoming available in commercial SPECT/CT devices. This study's goal was to assess quantitative accuracy of activity recovery as a function of image reconstruction parameters and count statistics in ...
Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning.
PloS one
Oct 11, 2016
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...
Demography
Humans
Anthropometry
Adiponectin
Triglycerides
Incidence
Black or African American
Adult
Diabetes Mellitus, Type 2
Machine Learning
Male
C-Reactive Protein
Models, Theoretical
Leptin
Biomarkers
Middle Aged
Glycated Hemoglobin
Follow-Up Studies
Waist Circumference
Female
Blood Glucose
Cholesterol, HDL
Aged
Estimation of umbilical cord blood leptin and insulin based on anthropometric data by means of artificial neural network approach: identifying key maternal and neonatal factors.
BMC pregnancy and childbirth
Jul 21, 2016
BACKGROUND: Leptin and insulin levels are key factors regulating fetal and neonatal energy homeostasis, development and growth. Both biomarkers are used as predictors of weight gain and obesity during infancy. There are currently no prediction algori...
A Prognosis Tool Based on Fuzzy Anthropometric and Questionnaire Data for Obstructive Sleep Apnea Severity.
Journal of medical systems
Mar 1, 2016
Obstructive sleep apnea (OSA) are linked to the augmented risk of morbidity and mortality. Although polysomnography is considered a well-established method for diagnosing OSA, it suffers the weakness of time consuming and labor intensive, and require...
LOPES II--Design and Evaluation of an Admittance Controlled Gait Training Robot With Shadow-Leg Approach.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 31, 2015
Robotic gait training is gaining ground in rehabilitation. Room for improvement lies in reducing donning and doffing time, making training more task specific and facilitating active balance control, and by allowing movement in more degrees of freedom...
Two-year longitudinal health-related fitness, anthropometry and body composition status amongst adolescents in Tlokwe Municipality: The PAHL Study.
African journal of primary health care & family medicine
Oct 30, 2015
AIM: To evaluate a two-year longitudinal development of health-related fitness, anthropometry and body composition status amongst adolescents in Tlokwe Municipality, Potchefstroom, South Africa.
Cost-Sensitive Local Binary Feature Learning for Facial Age Estimation.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sep 23, 2015
In this paper, we propose a cost-sensitive local binary feature learning (CS-LBFL) method for facial age estimation. Unlike the conventional facial age estimation methods that employ hand-crafted descriptors or holistically learned descriptors for fe...
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