Machine learning for classification of hypertension subtypes using multi-omics: a multi-centre, retrospective, data-driven study (original) (raw)

Authors:

Reel, P. S., Reel, S., van Kralingen, J. C., Langton, K., Lang, K., Erlic, Z., Larsen, C. K., Amar, L., Pamporaki, C., Mulatero, P., Blanchard, A., Kabat, M., Robertson, S., MacKenzie, S. M., Taylor, A. E., Peitzsch, M., Ceccato, F., Scaroni, C., Reincke, M., Kroiss, M., Dennedy, M. C., Pecori, A., Monticone, S., Deinum, J., Rossi, G. P., Lenzini, L., McClure, J. D., Nind, T., Riddell, A., Stell, A., Cole, C., Sudano, I., Prehn, C., Adamski, J., Gimenez-Roqueplo, A.-P., Assié, G., Arlt, W., Beuschlein, F., Eisenhofer, G., Davies, E., Zennaro, M.-C., and Jefferson, E.

Copyright Holders:

Copyright © 2022 The Authors

First Published:

First published in EBioMedicine 84: 104276

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Reproduced under a Creative Commons License