Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

H.S. Muti; L.R. Heij; G. Keller; M. Kohlruss; R. Langer; B. Dislich; J.H. Cheong; Y.W. Kim; H. Kim; M.C. Kook; D. Cunningham; W.H. Allum; R.E. Langley; M.G. Nankivell; P. Quirke; J.D. Hayden; N.P. West; A.J. Irvine; T. Yoshikawa; T. Oshima; R. Huss; B. Grosser; F. Roviello; A. d'Ignazio; A. Quaas; H. Alakus; X.X. Tan; A.T. Pearson; T. Luedde; M.P. Ebert; D. Jager; C. Trautwein; N.T. Gaisa; H.I. Grabsch; J.N. Kather

doi:10.1016/S2589-7500(21)00133-3

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

H.S. Muti, L.R. Heij, G. Keller, M. Kohlruss, R. Langer, B. Dislich, J.H. Cheong, Y.W. Kim, H. Kim, M.C. Kook, D. Cunningham, W.H. Allum, R.E. Langley, M.G. Nankivell, P. Quirke, J.D. Hayden, N.P. West, A.J. Irvine, T. Yoshikawa, T. OshimaR. Huss, B. Grosser, F. Roviello, A. d'Ignazio, A. Quaas, H. Alakus, X.X. Tan, A.T. Pearson, T. Luedde, M.P. Ebert, D. Jager, C. Trautwein, N.T. Gaisa, H.I. Grabsch, J.N. Kather^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

5 Citations (Web of Science)

Original language	English
Pages (from-to)	E654-E664
Number of pages	11
Journal	The Lancet Digital Health
Volume	3
Issue number	10
DOIs	https://doi.org/10.1016/S2589-7500(21)00133-3
Publication status	Published - 1 Oct 2021

Keywords

MICROSATELLITE INSTABILITY
GASTRIC-CANCER

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Muti, H. S., Heij, L. R., Keller, G., Kohlruss, M., Langer, R., Dislich, B., Cheong, J. H., Kim, Y. W., Kim, H., Kook, M. C., Cunningham, D., Allum, W. H., Langley, R. E., Nankivell, M. G., Quirke, P., Hayden, J. D., West, N. P., Irvine, A. J., Yoshikawa, T., ... Kather, J. N. (2021). Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study. The Lancet Digital Health, 3(10), E654-E664. https://doi.org/10.1016/S2589-7500(21)00133-3

Muti, H.S. ; Heij, L.R. ; Keller, G. ; Kohlruss, M. ; Langer, R. ; Dislich, B. ; Cheong, J.H. ; Kim, Y.W. ; Kim, H. ; Kook, M.C. ; Cunningham, D. ; Allum, W.H. ; Langley, R.E. ; Nankivell, M.G. ; Quirke, P. ; Hayden, J.D. ; West, N.P. ; Irvine, A.J. ; Yoshikawa, T. ; Oshima, T. ; Huss, R. ; Grosser, B. ; Roviello, F. ; d'Ignazio, A. ; Quaas, A. ; Alakus, H. ; Tan, X.X. ; Pearson, A.T. ; Luedde, T. ; Ebert, M.P. ; Jager, D. ; Trautwein, C. ; Gaisa, N.T. ; Grabsch, H.I. ; Kather, J.N. / Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study. In: The Lancet Digital Health. 2021 ; Vol. 3, No. 10. pp. E654-E664.

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author = "H.S. Muti and L.R. Heij and G. Keller and M. Kohlruss and R. Langer and B. Dislich and J.H. Cheong and Y.W. Kim and H. Kim and M.C. Kook and D. Cunningham and W.H. Allum and R.E. Langley and M.G. Nankivell and P. Quirke and J.D. Hayden and N.P. West and A.J. Irvine and T. Yoshikawa and T. Oshima and R. Huss and B. Grosser and F. Roviello and A. d'Ignazio and A. Quaas and H. Alakus and X.X. Tan and A.T. Pearson and T. Luedde and M.P. Ebert and D. Jager and C. Trautwein and N.T. Gaisa and H.I. Grabsch and J.N. Kather",

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Muti, HS, Heij, LR, Keller, G, Kohlruss, M, Langer, R, Dislich, B, Cheong, JH, Kim, YW, Kim, H, Kook, MC, Cunningham, D, Allum, WH, Langley, RE, Nankivell, MG, Quirke, P, Hayden, JD, West, NP, Irvine, AJ, Yoshikawa, T, Oshima, T, Huss, R, Grosser, B, Roviello, F, d'Ignazio, A, Quaas, A, Alakus, H, Tan, XX, Pearson, AT, Luedde, T, Ebert, MP, Jager, D, Trautwein, C, Gaisa, NT, Grabsch, HI & Kather, JN 2021, 'Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study', The Lancet Digital Health, vol. 3, no. 10, pp. E654-E664. https://doi.org/10.1016/S2589-7500(21)00133-3

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study. / Muti, H.S.; Heij, L.R.; Keller, G.; Kohlruss, M.; Langer, R.; Dislich, B.; Cheong, J.H.; Kim, Y.W.; Kim, H.; Kook, M.C.; Cunningham, D.; Allum, W.H.; Langley, R.E.; Nankivell, M.G.; Quirke, P.; Hayden, J.D.; West, N.P.; Irvine, A.J.; Yoshikawa, T.; Oshima, T.; Huss, R.; Grosser, B.; Roviello, F.; d'Ignazio, A.; Quaas, A.; Alakus, H.; Tan, X.X.; Pearson, A.T.; Luedde, T.; Ebert, M.P.; Jager, D.; Trautwein, C.; Gaisa, N.T.; Grabsch, H.I.; Kather, J.N.

In: The Lancet Digital Health, Vol. 3, No. 10, 01.10.2021, p. E654-E664.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

AU - Muti, H.S.

AU - Heij, L.R.

AU - Keller, G.

AU - Kohlruss, M.

AU - Langer, R.

AU - Dislich, B.

AU - Cheong, J.H.

AU - Kim, Y.W.

AU - Kim, H.

AU - Kook, M.C.

AU - Cunningham, D.

AU - Allum, W.H.

AU - Langley, R.E.

AU - Nankivell, M.G.

AU - Quirke, P.

AU - Hayden, J.D.

AU - West, N.P.

AU - Irvine, A.J.

AU - Yoshikawa, T.

AU - Oshima, T.

AU - Huss, R.

AU - Grosser, B.

AU - Roviello, F.

AU - d'Ignazio, A.

AU - Quaas, A.

AU - Alakus, H.

AU - Tan, X.X.

AU - Pearson, A.T.

AU - Luedde, T.

AU - Ebert, M.P.

AU - Jager, D.

AU - Trautwein, C.

AU - Gaisa, N.T.

AU - Grabsch, H.I.

AU - Kather, J.N.

PY - 2021/10/1

Y1 - 2021/10/1

KW - MICROSATELLITE INSTABILITY

KW - GASTRIC-CANCER

U2 - 10.1016/S2589-7500(21)00133-3

DO - 10.1016/S2589-7500(21)00133-3

M3 - Article

VL - 3

SP - E654-E664

JO - The Lancet Digital Health

JF - The Lancet Digital Health

SN - 2589-7500

IS - 10

ER -