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[3AW-12-7] Machine learning approach for discrimination of genotypes based on bright-field cellular images

Godai Suzuki1, Yutaka Saito2, 3, 4, Motoaki Seki5, Daniel YamamotoEvans5, 6, 7, Mikiko Negishi5, Kentaro Kakoi5, Hiroki Kawai8, Christian Landry9, 10, 11, 12, 13, Nozomu Yachie5, 6, 7, 14, Toutai Mitsuyama2 (1.Synecoculture Assoc., 2.AIRC, AIST, 3.CBBD-OIL, AIST, 4.Grad. Sch. of Front. Sci.,Univ. of Tokyo, 5.Res. C. for Adv. Sci. Tech., Univ. of Tokyo, 6.Inst. for Adv. Biosci., Keio Univ., 7.Sys. Biol. Prog., Grad. Sch. of Media and Gov., Keio Univ., 8.Res. Dev. Dept., LPIXEL Inc., 9.Inst. de Biol. Integ. et des Sys., Univ. Laval, 10.Dept. de Biochem., Microbiol. et Bio-info., Facul. de sci. et genie, Univ. Laval, 11.PROTEO, Univ. Laval, 12.CRDM, Univ. Laval, 13.Dept. de Biol., Faculte des sci. et de Genie, Univ. Laval, 14.Sch. of Biomed. Eng., The Univ. of British Columbia)

g . Imaging(5 . Information / System / Technology)

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