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Full-Text Articles in Social and Behavioral Sciences
Prediction Model Of A Joint Analysis Of Beef Growth And Carcass Quality Traits, H R. Mirzaei, Arunas P. Verbyla, Wayne S. Pitchford
Prediction Model Of A Joint Analysis Of Beef Growth And Carcass Quality Traits, H R. Mirzaei, Arunas P. Verbyla, Wayne S. Pitchford
Faculty of Engineering and Information Sciences - Papers: Part A
A joint growth-carcass analysis was conducted to develop equations for predicting carcass quality traits associated with variation in growth path of crossbred cattle. During a four-year period (1994-1997) of the Australian "Southern Crossbreeding Project", mature Hereford cows (r = 581) were mated to 97 sires of Jersey, Wagyu, Angus, Hereford, South Devon, Limousin, and Belgian Blue breeds, resulting in 1141 calves. Data included body weight measurements of steers and heifers from birth until slaughter and four carcass quality traits: hot standard carcass weight, rump fat depth, rib eye muscle area, and intramuscular fat content. The model provides nine outputs: median …
Hierarchical Anatomical Brain Networks For Mci Prediction: Revisiting Volumetric Measures, Luping Zhou, Yaping Wang, Yang Li, Pew-Thian Yap, Dinggang Shen, Alzheimers Disease Neuroimaging Initiative (Adni)
Hierarchical Anatomical Brain Networks For Mci Prediction: Revisiting Volumetric Measures, Luping Zhou, Yaping Wang, Yang Li, Pew-Thian Yap, Dinggang Shen, Alzheimers Disease Neuroimaging Initiative (Adni)
Faculty of Engineering and Information Sciences - Papers: Part A
Owning to its clinical accessibility, T1-weighted MRI (Magnetic Resonance Imaging) has been extensively studied in the past decades for prediction of Alzheimer's disease (AD) and mild cognitive impairment (MCI). The volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) are the most commonly used measurements, resulting in many successful applications. It has been widely observed that disease-induced structural changes may not occur at isolated spots, but in several inter-related regions. Therefore, for better characterization of brain pathology, we propose in this paper a means to extract inter-regional correlation based features from local volumetric measurements. Specifically, our approach …
Hierarchical Anatomical Brain Networks For Mci Prediction By Partial Least Square Analysis, Luping Zhou, Yaping Wang, Yang Li, Pew-Thian Yap, Dinggang Shen
Hierarchical Anatomical Brain Networks For Mci Prediction By Partial Least Square Analysis, Luping Zhou, Yaping Wang, Yang Li, Pew-Thian Yap, Dinggang Shen
Faculty of Engineering and Information Sciences - Papers: Part A
Owning to its clinical accessibility, T1-weighted MRI has been extensively studied for the prediction of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The tissue volumes of GM, WM and CSF are the most commonly used measures for MCI and AD prediction. We note that disease-induced structural changes may not happen at isolated spots, but in several inter-related regions. Therefore, in this paper we propose to directly extract the inter-region connectivity based features for MCI prediction. This involves constructing a brain network for each subject, with each node representing an ROI and each edge representing regional interactions. This network is …