Song, Wanqing,
Chen, Jianxue,
Wang, Zhen,
Kudreyko, Aleksey,
Qi, Deyu,
Zio, Enrico (2023) of Maryland CALEC
dataset. Our forecasting
results demonstrate the high accuracy of the method and its
and determining the volume of inhomogeneity.
Datasets from the public database MosMedData and NSCLC were used
Chu, Shuk Han,
Zhao, Xu,
Komber, Ahmad,
Cheyne, Joshua,
Wu, Simiao,
Cowey, Eileen,
Kutlubaev, Mansur,
Mead, Gillian (2023) included mood and quality of life.
Results: We screened 33,297 citations and identified 10 published
Timasheva, Y.,
Balkhiyarova, Z.,
Avzaletdinova, D.,
Rassoleeva, I.,
Morugova, T.V.,
Korytina, G.,
Prokopenko, I.,
Kochetova, O. (2023) ability of the model containing polygenic scores for the variants associated with T2D in our
datasetKazantseva, Anastasiya,
Davydova, Yuliya,
Enikeeva, Renata,
Mustafin, Rustam,
Malykh, Sergey,
Lobaskova, Marina,
Kanapin, Alexander,
Prokopenko, Inga,
Khusnutdinova, Elza (2023) sensitivity to evaluate depression level in the full
dataset, explaining up to 2.4% of the variance (p = 3