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FORTANER UYÀ, LIDIA

FORTANER UYÀ, LIDIA  

Facoltà di Psicologia  

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A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study 1-gen-2025 Fortaner-Uyà, L.; Monopoli, C.; Cavicchioli, M.; Calesella, F.; Colombo, F.; Carretta, I.; Talè, C.; Benedetti, F.; Visintini, R.; Maffei, C.; Vai, B.
A machine learning pipeline for efficient differentiation between bipolar and major depressive disorder based on multimodal structural neuroimaging 1-gen-2024 Calesella, F.; Colombo, F.; Bravi, B.; Fortaner-Uya, L.; Monopoli, C.; Poletti, S.; Tassi, E.; Maggioni, E.; Brambilla, P.; Colombo, C.; Bollettini, I.; Benedetti, F.; Vai, B.
A machine learning pipeline for efficient differentiation between depressed bipolar disorder and major depressive disorder patients based on structural neuroimaging 1-gen-2022 Calesella, F.; Colombo, F.; Bravi, B.; Fortaner-Uyà, L.; Monopoli, C.; Tassi, E.; Maggioni, E.; Bollettini, I.; Poletti, S.; Vai, B.; Benedetti, F.
Association between NTRK2 Polymorphisms, Hippocampal Volumes and Treatment Resistance in Major Depressive Disorder 1-gen-2023 Paolini, M.; Fortaner-Uyà, L.; Lorenzi, C.; Spadini, S.; Maccario, M.; Zanardi, R.; Colombo, C.; Poletti, S.; Benedetti, F.
Beyond the Global Brain Differences: Intra-individual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers 1-gen-2024 Boen, Rune; Kaufmann, Tobias; van der Meer, Dennis; Frei, Oleksandr; Agartz, Ingrid; Ames, David; Andersson, Micael; Armstrong, Nicola J; Artiges, Eric; Atkins, Joshua R; Bauer, Jochen; Benedetti, Francesco; Boomsma, Dorret I; Brodaty, Henry; Brosch, Katharina; Buckner, Randy L; Cairns, Murray J; Calhoun, Vince; Caspers, Svenja; Cichon, Sven; Corvin, Aiden P; Facorro, Benedicto Crespo; Dannlowski, Udo; David, Friederike S; de Geus, Eco J C; de Zubicaray, Greig I; Desrivières, Sylvane; Doherty, Joanne L; Donohoe, Gary; Ehrlich, Stefan; Eising, Else; Espeseth, Thomas; Fisher, Simon E; Forstner, Andreas J; Uyà, Lidia Fortaner; Frouin, Vincent; Fukunaga, Masaki; Ge, Tian; Glahn, David C; Goltermann, Janik; Grabe, Hans J; Green, Melissa J; Groenewold, Nynke A; Grotegerd, Dominik; Hahn, Tim; Hashimoto, Ryota; Hehir-Kwa, Jayne Y; Henskens, Frans A; Holmes, Avram J; Haberg, Asta K; Haavik, Jan; Jacquemont, Sebastien; Jansen, Andreas; Jockwitz, Christiane; Jonsson, Erik G; Kikuchi, Masataka; Kircher, Tilo; Kumar, Kuldeep; Le Hellard, Stephanie; Leu, Costin; Linden, David E; Liu, Jingyu; Loughnan, Robert; Mather, Karen A; Mcmahon, Katie L; Mcrae, Allan F; Medland, Sarah E; Meinert, Susanne; Moreau, Clara A; Morris, Derek W; Mowry, Bryan J; Muhleisen, Thomas W; Nenadić, Igor; Nöthen, Markus M; Nyberg, Lars; Owen, Michael J; Paolini, Marco; Paus, Tomas; Pausova, Zdenka; Persson, Karin; Quidé, Yann; Marques, Tiago Reis; Sachdev, Perminder S; Sando, Sigrid B; Schall, Ulrich; Scott, Rodney J; Selbæk, Geir; Shumskaya, Elena; Silva, Ana I; Sisodiya, Sanjay M; Stein, Frederike; Stein, Dan J; Straube, Benjamin; Streit, Fabian; Strike, Lachlan T; Teumer, Alexander; Teutenberg, Lea; Thalamuthu, Anbupalam; Tooney, Paul A; Tordesillas-Gutierrez, Diana; Trollor, Julian N; Ent, Dennis van 't; van den Bree, Marianne B M; van Haren, Neeltje E M; Vazquez-Bourgon, Javier; Volzke, Henry; Wen, Wei; Wittfeld, Katharina; Ching, Christopher R K; Westlye, Lars T; Thompson, Paul M; Bearden, Carrie E; Selmer, Kaja K; Alnæs, Dag; Andreassen, Ole A; Sonderby, Ida E
Cognitive distortions and structural neuroimaging data predict depression severity in unipolar and bipolar depression: a machine learning study 1-gen-2023 Perziani, S.; Colombo, F.; Calesella, F.; Fortaner-Uyà, L.; Monopoli, C.; Bravi, B.; Poletti, S.; Bollettini, I.; Benedetti, F.; Vai, B.
Combining clinical data, genetics, and adverse childhood experiences for suicidality prediction in mood disorders: a machine learning approach 1-gen-2023 Fortaner-Uyà, L.; Mazzilli, F.; Monopoli, C.; Calesella, F.; Colombo, F.; Bravi, B.; Fabbri, C.; Serretti, A.; Lorenzi, C.; Spadini, S.; Mascia, E.; Poletti, S.; Bollettini, I.; Benedetti, F.; Vai, B.
Data-driven stratification of depressed patients based on structural neuroimaging signatures: a stability-based relative clustering validation approach 1-gen-2022 Colombo, F.; Calesella, F.; Bravi, B.; Fortaner-Uyà, L.; Monopoli, C.; Maggioni, E.; Tassi, E.; Zanardi, R.; Attanasio, F.; Bollettini, I.; Poletti, S.; Vai, B.; Benedetti, F.
Disentangling the Genetic Landscape of Peripartum Depression: A Multi-Polygenic Machine Learning Approach on an Italian Sample 1-gen-2024 Harrington, Y. A.; Fortaner-Uya, L.; Paolini, M.; Poletti, S.; Lorenzi, C.; Spadini, S.; Melloni, E. M. T.; Agnoletto, E.; Zanardi, R.; Colombo, C.; Benedetti, F.
Functional neuroimaging for the differentiation between healthy controls, depressed bipolar and major depressive patients: a machine learning study 1-gen-2023 Calesella, F.; Serra, E.; Colombo, F.; Fortaner-Uyà, L.; Monopoli, C.; Bravi, B.; Tassi, E.; Bollettini, I.; Brambilla, P.; Poletti, S.; Maggioni, E.; Benedetti, F.; Vai, B.
History of Peripartum Depression Moderates the Association Between Estradiol Polygenic Risk Scores and Basal Ganglia Volumes in Major Depressive Disorder 1-gen-2025 Harrington, Y. A.; Paolini, M.; Fortaner-Uya, L.; Maccario, M.; Melloni, E. M. T.; Poletti, S.; Lorenzi, C.; Zanardi, R.; Colombo, C.; Benedetti, F.
Identifying suicide attempters among bipolar depressed patients using structural neuroimaging: a machine learning study 1-gen-2022 Fortaner-Uyà, L.; Monopoli, C.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Poletti, S.; Bollettini, I.; Vai, B.; Benedetti, F.
Moving beyond clinical approaches: machine learning on neuroimaging and cognitive features for the differential diagnosis between unipolar and bipolar depression 1-gen-2023 Serra, E.; Calesella, F.; Colombo, F.; Bravi, B.; Fortaner-Uyà, L.; Monopoli, C.; Poletti, S.; Bollentini, I.; Benedetti, F.; Vai, B.
Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance 1-gen-2024 Colombo, F.; Calesella, F.; Bravi, B.; Fortaner-Uya, L.; Monopoli, C.; Tassi, E.; Carminati, M.; Zanardi, R.; Bollettini, I.; Poletti, S.; Lorenzi, C.; Spadini, S.; Brambilla, P.; Serretti, A.; Maggioni, E.; Fabbri, C.; Benedetti, F.; Vai, B.
Predicting cognitive impairment in depression: a machine learning approach on multimodal structural neuroimaging 1-gen-2023 Monopoli, C.; Calesella, F.; Verri, A.; Fortaner-Uyà, L.; Colombo, F.; Bravi, B.; Bollettini, I.; Poletti, S.; Benedetti, F.; Vai, B.
Predicting Suicide Attempts among Major Depressive Disorder Patients with Structural Neuroimaging: A Machine Learning Approach 1-gen-2023 Fortaner-Uyà, L.; Monopoli, C.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Poletti, S.; Bollettini, I.; Benedetti, F.; Vai, B.
Predicting unipolar and bipolar depression using inflammatory markers, neuroimaging and neuropsychological data: a machine learning study 1-gen-2023 Raffaelli, L.; Colombo, F.; Calesella, F.; Fortaner-Uya, L.; Bollettini, I.; Lorenzi, C.; Maggioni, E.; Tassi, E.; Poletti, S.; Zanardi, R.; Attanasio, F.; Benedetti, F.; Vai, B.
Prediction of cognitive impairment in mood disorders using multimodal structural neuroimaging: a machine learning study 1-gen-2022 Monopoli, C.; Fortaner-Uyà, L.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Bollettini, I.; Poletti, S.; Vai, B.; Benedetti, F.
Reduced corticolimbic habituation to negative stimuli characterizes bipolar depressed suicide attempters 1-gen-2023 Vai, B.; Calesella, F.; Lenti, C.; Fortaner-Uyà, L.; Caselani, E.; Fiore, P.; Breit, S.; Poletti, S.; Colombo, C.; Zanardi, R.; Benedetti, F.
Unsupervised neurobiologically-driven stratification of clinical heterogeneity in treatment-resistant depression 1-gen-2023 Colombo, F.; Calesella, F.; Bravi, B.; Fortaner-Uyà, L.; Monopoli, C.; Carminati, M.; Zanardi, R.; Bollettini, I.; Poletti, S.; Benedetti, F.; Vai, B.