Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA)

Por Engchuan, Worrawat, Dimopoulos, Alexandros C., Tyrovolas, Stefanos, Caballero, Francisco Félix, Sanchez-Niubo, Albert, Arndt, Holger, Ayuso-Mateos, Jose Luis, Haro, Josep Maria, Chatterji, Somnath, Panagiotakos, Demosthenes B.
Publicado no Med Sci Monit (2019)

Exome Sequencing in BRCA1- and BRCA2-Negative Greek Families Identifies MDM1 and NBEAL1 as Candidate Risk Genes for Hereditary Breast Cancer

Por Glentis, Stavros, Dimopoulos, Alexandros C., Rouskas, Konstantinos, Ntritsos, George, Evangelou, Evangelos, Narod, Steven A., Mes-Masson, Anne-Marie, Foulkes, William D., Rivera, Barbara, Tonin, Patricia N., Ragoussis, Jiannis, Dimas, Antigone S.
Publicado no Front Genet (2019)

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk

Por Dimopoulos, Alexandros C., Nikolaidou, Mara, Caballero, Francisco Félix, Engchuan, Worrawat, Sanchez-Niubo, Albert, Arndt, Holger, Ayuso-Mateos, José Luis, Haro, Josep Maria, Chatterji, Somnath, Georgousopoulou, Ekavi N., Pitsavos, Christos, Panagiotakos, Demosthenes B.
Publicado no BMC Med Res Methodol (2018)

Ten simple rules for making training materials FAIR

Por Garcia, Leyla, Batut, Bérénice, Burke, Melissa L., Kuzak, Mateusz, Psomopoulos, Fotis, Arcila, Ricardo, Attwood, Teresa K., Beard, Niall, Carvalho-Silva, Denise, Dimopoulos, Alexandros C., del Angel, Victoria Dominguez, Dumontier, Michel, Gurwitz, Kim T., Krause, Roland, McQuilton, Peter, Le Pera, Loredana, Morgan, Sarah L., Rauste, Päivi, Via, Allegra, Kahlem, Pascal, Rustici, Gabriella, van Gelder, Celia W. G., Palagi, Patricia M.
Publicado no PLoS Comput Biol (2020)