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The Lancet : Digital health

ISSNs: 2589-7500

Additional searchable ISSN (electronic): 2589-7500

The Lancet, United Kingdom

Scopus rating (2023): CiteScore 41.2 SJR 7.277 SNIP 5.367

Journal

Titles	The Lancet : Digital health(2019 → …) The Lancet Digital Health
Additional searchable titles	Lancet Digit Health
ISSNs	2589-7500
Additional searchable ISSN (electronic)	2589-7500
Publisher	The Lancet
Country/Territory	United Kingdom
ZDB-ID	2972368-1

Keywords

ASJC Scopus subject areas

Library keywords

610 Medicine and health

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study

Jiang, X., Hoffmeister, M., Brenner, H., Muti, H. S., Yuan, T., Foersch, S., West, N. P., & 12 othersBrobeil, A., Jonnagaddala, J., Hawkins, N., Ward, R. L., Brinker, T. J., Saldanha, O. L., Ke, J., Müller, W., Grabsch, H. I., Quirke, P., Truhn, D. & Kather, J. N., Jan 2024, In: The Lancet Digital Health. 6, 1, p. e33-e43

Research output: Contribution to journal › Research article › Contributed › peer-review

Prediction of metastatic pheochromocytoma and paraganglioma: A machine learning modelling study using data from a cross-sectional cohort

Pamporaki, C., Berends, A. M. A., Filippatos, A., Prodanov, T., Meuter, L., Prejbisz, A., Beuschlein, F., & 16 othersFassnacht, M., Timmers, H. J. L. M., Nölting, S., Abhyankar, K., Constantinescu, G., Kunath, C., de Haas, R. J., Wang, K., Remde, H., Bornstein, S. R., Januszewicz, A., Robledo, M., Lenders, J. W. M., Kerstens, M. N., Pacak, K. & Eisenhofer, G., Sept 2023, In: The Lancet : Digital health. 5, 9, p. e551-e559 9 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study

Kers, J., Bülow, R. D., Klinkhammer, B. M., Breimer, G. E., Fontana, F., Abiola, A. A., Hofstraat, R., & 16 othersCorthals, G. L., Peters-Sengers, H., Djudjaj, S., von Stillfried, S., Hölscher, D. L., Pieters, T. T., van Zuilen, A. D., Bemelman, F. J., Nurmohamed, A. S., Naesens, M., Roelofs, J. J. T. H., Florquin, S., Floege, J., Nguyen, T. Q., Kather, J. N. & Boor, P., Jan 2022, In: The Lancet Digital Health. 4, 1, p. e18-e26

Research output: Contribution to journal › Research article › Contributed › peer-review

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., & 28 othersKim, 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., Pearson, A. T., Luedde, T., Ebert, M. P., Jäger, D., Trautwein, C., Gaisa, N. T., Grabsch, H. I. & Kather, J. N., Oct 2021, In: The Lancet Digital Health. 3, 10, p. e654-e664

Research output: Contribution to journal › Research article › Contributed › peer-review

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