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| Maciukiewicz M, Marshe V, Hauschild A, et al. (2019) GWAS-BASED MACHINE LEARNING APPROACH TO PREDICT DULOXETINE RESPONSE AND REMISSION IN MAJOR DEPRESSIVE DISORDER European Neuropsychopharmacology. 29: S843 |
| Maciukiewicz M, Marshe VS, Hauschild AC, et al. (2018) GWAS-based machine learning approach to predict duloxetine response in major depressive disorder. Journal of Psychiatric Research. 99: 62-68 |
| Lam RW, Milev R, Rotzinger S, et al. (2016) Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort. Bmc Psychiatry. 16: 105 |
| Salomons TV, Dunlop K, Kennedy SH, et al. (2014) Resting-state cortico-thalamic-striatal connectivity predicts response to dorsomedial prefrontal rTMS in major depressive disorder. Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology. 39: 488-98 |
| Downar J, Bakker N, Geraci J, et al. (2013) 1571 – Efficacy of rTMS of the dorsomedial prefrontal cortex on binge-purge behaviors in refractory anorexia and bulimia nervosa: a case series European Psychiatry. 28: 1 |
| Geraci J, Lidar DA. (2010) Classical lsing model test for quantum circuits New Journal of Physics. 12 |
| Geraci J. (2008) A new connection between quantum circuits, graphs and the Ising partition function Quantum Information Processing. 7: 227-242 |
| Geraci J, Lidar DA. (2008) On the exact evaluation of certain instances of the potts partition function by quantum computers Communications in Mathematical Physics. 279: 735-768 |