Nunes, Abraham; Schnack, Hugo G.; Ching, Christopher R.K.; Agartz, Ingrid; Akudjedu, Theophilus N.; Alda, Martin; Alnæs, Dag; Alonso-Lana, Silvia; Bauer, Jochen; Baune, Bernhard T.; Bøen, Erlend; Bonnin, Caterina del Mar; Busatto, Geraldo F.; Canales-Rodríguez, Erick J.; Cannon, Dara M.; Caseras, Xavier; Chaim-Avancini, Tiffany M.; Dannlowski, Udo; Díaz-Zuluaga, Ana M.; Dietsche, Bruno; Doan, Nhat Trung; Duchesnay, Edouard; Elvsåshagen, Torbjørn; Emden, Daniel; Eyler, Lisa T.; Fatjó-Vilas, Mar; Favre, Pauline; Foley, Sonya F.; Fullerton, Janice M.; Glahn, David C.; Goikolea, Jose M.; Grotegerd, Dominik; Hahn, Tim; Henry, Chantal; Hibar, Derrek P.; Houenou, Josselin; Howells, Fleur M.; Jahanshad, Neda; Kaufmann, Tobias; Kenney, Joanne; Kircher, Tilo T.J.; Krug, Axel; Lagerberg, Trine V.; Lenroot, Rhoshel K.; López-Jaramillo, Carlos; Machado-Vieira, Rodrigo; Malt, Ulrik F.; McDonald, Colm; Mitchell, Philip B.; van Haren, Neeltje E.M.; for the ENIGMA Bipolar Disorders Working Group
(Springer Nature, 2020-09)
Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings ...