Automatic quality control of corpus callosum segmentations in large population studies

2020 ◽  
Author(s):  
William Javier García Herrera
Keyword(s):  
Quality Control ◽  
Corpus Callosum ◽  
Population Studies ◽  
Large Population ◽  
Automatic Quality Control

scholarly journals Automatic quality control and enhancement for voice-based remote Parkinson’s disease detection

2021 ◽  
Vol 127 ◽  
pp. 1-16
Author(s):  
Amir Hossein Poorjam ◽  
Mathew Shaji Kavalekalam ◽  
Liming Shi ◽  
Jordan P. Raykov ◽  
Jesper Rindom Jensen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Quality Control ◽  
Disease Detection ◽  
Automatic Quality Control

scholarly journals Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse

2021 ◽  
pp. 102219
Author(s):  
Simona Bottani ◽  
Ninon Burgos ◽  
Aurlien Maire ◽  
Adam Wild ◽  
Sebastian Strer ◽  
...  
Keyword(s):  
Quality Control ◽  
Magnetic Resonance ◽  
Data Warehouse ◽  
Clinical Data ◽  
Magnetic Resonance Images ◽  
Clinical Data Warehouse ◽  
Automatic Quality Control

Modular deep neural networks for automatic quality control of retinal optical coherence tomography scans

2021 ◽  
pp. 104822
Author(s):  
Josef Kauer-Bonin ◽  
Sunil K. Yadav ◽  
Ingeborg Beckers ◽  
Kay Gawlik ◽  
Seyedamirhosein Motamedi ◽  
...  
Keyword(s):  
Neural Networks ◽  
Quality Control ◽  
Optical Coherence Tomography ◽  
Deep Neural Networks ◽  
Optical Coherence ◽  
Automatic Quality Control

scholarly journals Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities

1998 ◽  
Vol 84 (1) ◽  
pp. 362-371 ◽  
Author(s):  
Roger G. Eston ◽  
Ann V. Rowlands ◽  
David K. Ingledew
Keyword(s):  
Heart Rate ◽  
Oxygen Uptake ◽  
Standard Error ◽  
Energy Cost ◽  
Population Studies ◽  
Large Population ◽  
Multiple Regression Equation ◽  
Heart Rate Monitoring ◽  
Children's Activities ◽  
Better Than

Eston, Roger G., Ann V. Rowlands, and David K. Ingledew.Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities. J. Appl. Physiol. 84(1): 362–371, 1998.—Heart rate telemetry is frequently used to estimate daily activity in children and to validate other methods. This study compared the accuracy of heart rate monitoring, pedometry, triaxial accelerometry, and uniaxial accelerometry for estimating oxygen consumption during typical children’s activities. Thirty Welsh children (mean age 9.2 ± 0.8 yr) walked (4 and 6 km/h) and ran (8 and 10 km/h) on a treadmill, played catch, played hopscotch, and sat and crayoned. Heart rate, body accelerations in three axes, pedometry counts, and oxygen uptake were measured continuously during each 4-min activity. Oxygen uptake was expressed as a ratio of body mass raised to the power of 0.75 [scaled oxygen uptake (sV˙o 2)]. All measures correlated significantly ( P < 0.001) with sV˙o 2. A multiple-regression equation that included triaxial accelerometry counts and heart rate predicted sV˙o 2 better than any measure alone ( R 2 = 0.85, standard error of the estimate = 9.7 ml ⋅ kg−0.75 ⋅ min−1). The best of the single measures was triaxial accelerometry ( R 2 = 0.83, standard error of the estimate = 10.3 ml ⋅ kg−0.75 ⋅ min−1). It is concluded that a triaxial accelerometer provides the best assessment of activity. Pedometry offers potential for large population studies.

scholarly journals Big health data: the new frontier for cardiovascular disease

2020 ◽  
pp. 4-7
Keyword(s):  
Cardiovascular Disease ◽  
Population Studies ◽  
Large Population ◽  
Cost Effective ◽  
Health Data ◽  
Health Care Administrators ◽  
Health Records ◽  
Traditional Research ◽  
New Frontier ◽  
The World

Despite improvement in diagnosis and management, cardiovascular disease (CVD) is the leading cause of death and hospitalization throughout the world. The expansion of digital cardiology presents outstanding opportunities for clinicians, researchers, and health care administrators to improve outcomes and sustainability of health systems. Electronic big health data combining electronic health records (EHRs) from diverse individuals across a wide variety of platforms may provide a real-time solution to questions and problems relating to health. Very large population studies based on EHR are efficient and cost-effective, and offer an alternative to traditional research approaches. Indeed, digital cardiology can help researchers to enhance, diagnose, and manage CVD using dedicated algorithms that allow targeted and personalized CVD treatments

Exploiting the Potential of Metabonomics in Large Population Studies: Three Venues

2007 ◽  
pp. 289-325 ◽  
Author(s):  
Burton H. Singer ◽  
Jürg Utzinger ◽  
Carol D. Ryff ◽  
Yulan Wang ◽  
Elaine Holmes
Keyword(s):  
Population Studies ◽  
Large Population

Improved phenotyping of apolipoprotein E: application to population frequency distribution

1990 ◽  
Vol 36 (11) ◽  
pp. 1871-1874 ◽  
Author(s):  
J S Hill ◽  
P H Pritchard
Keyword(s):  
Population Studies ◽  
Clinical Laboratory ◽  
Simple Procedure ◽  
Low Density Lipoprotein ◽  
Large Population ◽  
Density Lipoprotein ◽  
Lipid Clinic ◽  
Apo E ◽  
Slab Gels ◽  
Peroxidase Conjugate

Abstract A simple procedure for phenotyping apolipoprotein (apo) E directly from plasma has been developed for use in the lipid clinic laboratory. In this new method, 10 microL of serum or plasma is pretreated with neuraminidase (EC 3.2.1.18), which removes the sialic acid residues from apo E and eliminates additional bands, thereby ensuring correct phenotype assignment. After a rapid delipidation step, the samples are focused in vertical polyacrylamide mini-slab gels and immunoblotted with a polyclonal goat anti-apo E antibody, followed by a Protein G-peroxidase conjugate. The accuracy of this method was confirmed by comparison with the established procedure of phenotyping by isoelectric focusing of delipidated very-low-density lipoprotein. In addition, sera from 203 subjects from Vancouver, selected without conscious bias, were used to determine the local distribution of the apo E alleles. We estimate that the relative frequencies of apo E alleles epsilon 2, epsilon 3, and epsilon 4 in this population are 0.086, 0.761, and 0.153, respectively. The speed and convenience of using minigels make this procedure ideal for clinical laboratory applications and large population studies.

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