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A divisive hierarchical clustering methodology for enhancin..:
Barmpas, Petros
;
Tasoulis, Sotiris
;
Vrahatis, Aristidis G.
...
Health Information Science and Systems. 10 (2022) 1 - p. , 2022
Link:
https://doi.org/10.1007/s13755-022-00171-1
RT Journal T1
A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project
UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_s13755-022-00171-1&Exemplar=1&LAN=DE A1 Barmpas, Petros A1 Tasoulis, Sotiris A1 Vrahatis, Aristidis G. A1 Georgakopoulos, Spiros V. A1 Anagnostou, Panagiotis A1 Prina, Matthew A1 Ayuso-Mateos, José Luis A1 Bickenbach, Jerome A1 Bayes, Ivet A1 Bobak, Martin A1 Caballero, Francisco Félix A1 Chatterji, Somnath A1 Egea-Cortés, Laia A1 García-Esquinas, Esther A1 Leonardi, Matilde A1 Koskinen, Seppo A1 Koupil, Ilona A1 Paja̧k, Andrzej A1 Prince, Martin A1 Sanderson, Warren A1 Scherbov, Sergei A1 Tamosiunas, Abdonas A1 Galas, Aleksander A1 Haro, Josep Maria A1 Sanchez-Niubo, Albert A1 Plagianakos, Vassilis P. A1 Panagiotakos, Demosthenes PB Springer Science and Business Media LLC YR 2022 SN 2047-2501 JF Health Information Science and Systems VO 10 IS 1 LK http://dx.doi.org/https://doi.org/10.1007/s13755-022-00171-1 DO https://doi.org/10.1007/s13755-022-00171-1 SF ELIB - SuUB Bremen
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