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These three datasets were then combined using R statistical software to create one large population dataset spanning the years 3700 BC to 2000 AD.
OU-ISIR Large Population dataset.
OU-ISIR Gait Database, Large Population Dataset with Age.
We focused on the OU-ISIR Gait Database, Large Population Dataset.
Fig. 1 Examples of captured images in the OU-ISIR Gait Database, Large Population Dataset.
However, few large-scale databases are available for gait recognition, for example, the OU-ISIR Gait Database, Large Population Dataset [15] and Large Population Dataset with Bag, β version [22], which consider 4,007 and 2,070 subjects, respectively.
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Application of the models presented here to other large population datasets is needed to verify our findings.
[ 2, 3] In recent times data linking has been used to link large population datasets to further investigate health issues and trends in health and healthcare.
This study reaffirmed that manual matching is the "gold standard" for matching data, however, it is still inappropriate for large population datasets.
Detailed studies using large population datasets, applying different methods to detect selection using different aspects of the data and making use of massive sequence-based data, which will reduce the potential caveats related to SNP ascertainment bias, are now required.
Manual matching is seen as the "gold standard" in data linking, however this is often not feasible, if not impossible, due to the time consuming nature of the process, especially when using large population datasets.
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