Author

Yutaka Minowa

Tokyo Institute of Technology

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Neuroscience· 1

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Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:imaging· 1

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Hiroyuki AkamaiD· 1 shared Keiichi OnodaiD· 1 shared Masahiro TakamuraiD· 1 shared Naoki OkamotoiD· 1 shared Shuhei YamaguchiiD· 1 shared

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2022-2022 · peak 1/yr

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Hiroyuki AkamaORCID

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1 paper

Recent·Most cited

Comparing Deep Learning Models for Age Prediction Based on the Resting State fMRI Dataset from the "Brain Dock" Service in Japan

Yutaka Minowa, Keiichi Onoda, Masahiro Takamura, Shuhei Yamaguchi, Naoki Okamoto, Hiroyuki Akama

This study compares deep learning models for age prediction using resting-state fMRI data from the Japanese Brain Dock service, finding robust correlations across methods and highlighting the impact of atlas selection.

bioRxiv · Aug 14, 2022 · PreprintNeuroscience