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Oikonomou, E.K., Williams, M.C., Kotanidis, C.P., Desai, M.Y., Marwan, M., Antonopoulos, A.S., Thomas, K.E., Thomas, S., Akoumianakis, I., Fan, L.M., Kesavan, S., Herdman, L., Alashi, A., Centeno, E.H., Lyasheva, M., Griffin, B.P., Flamm, S.D., Shirodaria, C., Sabharwal, N., Kelion, A., Dweck, M.R., Van Beek, E.J.R., Deanfield, J., Hopewell, J.C., Neubauer, S., Channon, K.M., Achenbach, S., Newby, D.E. and Antoniades, C. (2019) A Novel Machine Learning-Derived Radiotranscriptomic Signature of Perivascular Fat Improves Cardiac Risk Prediction Using Coronary CT Angiography. European Heart Journal, 40, 3529-3543.
https://doi.org/10.1093/eurheartj/ehz592

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