BRAVI, BEATRICE
BRAVI, BEATRICE
Facoltà di Psicologia
A machine learning pipeline for efficient differentiation between depressed bipolar disorder and major depressive disorder patients based on structural neuroimaging
2022-01-01 Calesella, F.; Colombo, F.; Bravi, B.; Fortaner-Uyà, L.; Monopoli, C.; Tassi, E.; Maggioni, E.; Bollettini, I.; Poletti, S.; Vai, B.; Benedetti, F.
Abnormal choroid plexus, hippocampus, and lateral ventricles volumes as markers of treatment‐resistant major depressive disorder
2024-01-01 Bravi, Beatrice; Paolini, Marco; Maccario, Melania; Milano, Chiara; Raffaelli, Laura; Melloni, Elisa Maria Teresa; Zanardi, Raffaella; Colombo, Cristina; Benedetti, Francesco
Antidepressant chronotherapeutics normalizes prefrontal 1H-MRS glutamate in bipolar depression
2022-01-01 Melloni, Elisa M T; Bravi, Beatrice; Poletti, Sara; Dallaspezia, Sara; Barbini, Barbara; Zanardi, Raffaella; Benedetti, Francesco
Brain spectroscopic measures of glutamatergic and neuronal metabolism and glial activation influence white matter integrity in bipolar depression
2022-01-01 Bravi, Beatrice; Bollettini, Irene; Di Pasquasio, Camilla; Falini, Andrea; Zanardi, Raffaella; Poletti, Sara; Benedetti, Francesco; Colombo, Cristina
Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines
2024-01-01 Bravi, B; Melloni, Emt; Paolini, M; Palladini, M; Calesella, F; Servidio, L; Agnoletto, E; Poletti, S; Lorenzi, C; Colombo, C; Benedetti, F
Cognitive distortions and structural neuroimaging data predict depression severity in unipolar and bipolar depression: a machine learning study
2023-01-01 Perziani, S.; Colombo, F.; Calesella, F.; Fortaner-Uyà, L.; Monopoli, C.; Bravi, B.; Poletti, S.; Bollettini, I.; Benedetti, F.; Vai, B.
Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-of-concept study
2023-01-01 Palladini, Mariagrazia; Bravi, Beatrice; Colombo, Federica; Caselani, Elisa; Di Pasquasio, Camilla; D'Orsi, Greta; Rovere-Querini, Patrizia; Poletti, Sara; Benedetti, Francesco; Mazza, Mario Gennaro
Combining clinical data, genetics, and adverse childhood experiences for suicidality prediction in mood disorders: a machine learning approach
2023-01-01 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
2022-01-01 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.
Effect of glutamate excitotoxicity on white matter integrity in bipolar disorder: a TBSS study
2021-01-01 Bravi, B; Bollettini, I; Di Pasquasio, C; Conte, S; Zanardi, R; Benedetti, F; Poletti, S
Functional neuroimaging for the differentiation between healthy controls, depressed bipolar and major depressive patients: a machine learning study
2023-01-01 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.
Identifying suicide attempters among bipolar depressed patients using structural neuroimaging: a machine learning study
2022-01-01 Fortaner-Uyà, L.; Monopoli, C.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Poletti, S.; Bollettini, I.; Vai, B.; Benedetti, F.
Long-term effect of childhood trauma: Role of inflammation and white matter in mood disorders
2022-01-01 Poletti, Sara; Paolini, Marco; Ernst, Julia; Bollettini, Irene; Melloni, Elisa; Vai, Benedetta; Harrington, Yasmin; Bravi, Beatrice; Calesella, Federico; Lorenzi, Cristina; Zanardi, Raffaella; Benedetti, Francesco
Moving beyond clinical approaches: machine learning on neuroimaging and cognitive features for the differential diagnosis between unipolar and bipolar depression
2023-01-01 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
2024-01-01 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.
One-year mental health outcomes in a cohort of COVID-19 survivors
2022-01-01 Mazza, M. G.; Palladini, M.; De Lorenzo, R.; Bravi, B.; Poletti, S.; Furlan, R.; Ciceri, F.; Vai, B.; Bollettini, I.; Melloni, E. M. T.; Mazza, E. B.; Aggio, V.; Calesella, F.; Paolini, M.; Caselani, E.; Colombo, F.; D'Orsi, G.; Di Pasquasio, C.; Fiore, P.; Calvisi, S.; Canti, V.; Castellani, J.; Cilla, M.; Cinel, E.; Damanti, S.; Ferrante, M.; Martinenghi, S.; Santini, C.; Vitali, G.; Rovere-Querini, P.; Benedetti, F.
Persistent psychopathology in covid-19 survivors at one-year follow-up
2021-01-01 Mazza, Mg; Palladini, M; Bravi, B; Poletti, S; Rovere-Querini, P; Benedetti, F
Predicting cognitive impairment in depression: a machine learning approach on multimodal structural neuroimaging
2023-01-01 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
2023-01-01 Fortaner-Uyà, L.; Monopoli, C.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Poletti, S.; Bollettini, I.; Benedetti, F.; Vai, B.
Prediction of cognitive impairment in mood disorders using multimodal structural neuroimaging: a machine learning study
2022-01-01 Monopoli, C.; Fortaner-Uyà, L.; Calesella, F.; Colombo, F.; Bravi, B.; Maggioni, E.; Tassi, E.; Bollettini, I.; Poletti, S.; Vai, B.; Benedetti, F.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| 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. | |
| Abnormal choroid plexus, hippocampus, and lateral ventricles volumes as markers of treatment‐resistant major depressive disorder | 1-gen-2024 | Bravi, Beatrice; Paolini, Marco; Maccario, Melania; Milano, Chiara; Raffaelli, Laura; Melloni, Elisa Maria Teresa; Zanardi, Raffaella; Colombo, Cristina; Benedetti, Francesco | |
| Antidepressant chronotherapeutics normalizes prefrontal 1H-MRS glutamate in bipolar depression | 1-gen-2022 | Melloni, Elisa M T; Bravi, Beatrice; Poletti, Sara; Dallaspezia, Sara; Barbini, Barbara; Zanardi, Raffaella; Benedetti, Francesco | |
| Brain spectroscopic measures of glutamatergic and neuronal metabolism and glial activation influence white matter integrity in bipolar depression | 1-gen-2022 | Bravi, Beatrice; Bollettini, Irene; Di Pasquasio, Camilla; Falini, Andrea; Zanardi, Raffaella; Poletti, Sara; Benedetti, Francesco; Colombo, Cristina | |
| Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines | 1-gen-2024 | Bravi, B; Melloni, Emt; Paolini, M; Palladini, M; Calesella, F; Servidio, L; Agnoletto, E; Poletti, S; Lorenzi, C; Colombo, C; Benedetti, F | |
| 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. | |
| Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-of-concept study | 1-gen-2023 | Palladini, Mariagrazia; Bravi, Beatrice; Colombo, Federica; Caselani, Elisa; Di Pasquasio, Camilla; D'Orsi, Greta; Rovere-Querini, Patrizia; Poletti, Sara; Benedetti, Francesco; Mazza, Mario Gennaro | |
| 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. | |
| Effect of glutamate excitotoxicity on white matter integrity in bipolar disorder: a TBSS study | 1-gen-2021 | Bravi, B; Bollettini, I; Di Pasquasio, C; Conte, S; Zanardi, R; Benedetti, F; Poletti, S | |
| 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. | |
| 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. | |
| Long-term effect of childhood trauma: Role of inflammation and white matter in mood disorders | 1-gen-2022 | Poletti, Sara; Paolini, Marco; Ernst, Julia; Bollettini, Irene; Melloni, Elisa; Vai, Benedetta; Harrington, Yasmin; Bravi, Beatrice; Calesella, Federico; Lorenzi, Cristina; Zanardi, Raffaella; Benedetti, Francesco | |
| 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. | |
| One-year mental health outcomes in a cohort of COVID-19 survivors | 1-gen-2022 | Mazza, M. G.; Palladini, M.; De Lorenzo, R.; Bravi, B.; Poletti, S.; Furlan, R.; Ciceri, F.; Vai, B.; Bollettini, I.; Melloni, E. M. T.; Mazza, E. B.; Aggio, V.; Calesella, F.; Paolini, M.; Caselani, E.; Colombo, F.; D'Orsi, G.; Di Pasquasio, C.; Fiore, P.; Calvisi, S.; Canti, V.; Castellani, J.; Cilla, M.; Cinel, E.; Damanti, S.; Ferrante, M.; Martinenghi, S.; Santini, C.; Vitali, G.; Rovere-Querini, P.; Benedetti, F. | |
| Persistent psychopathology in covid-19 survivors at one-year follow-up | 1-gen-2021 | Mazza, Mg; Palladini, M; Bravi, B; Poletti, S; Rovere-Querini, P; Benedetti, F | |
| 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. | |
| 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. |