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Federico Calesella

Showing results (1-10 of 24) with videos related to

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Brain Informatics|April 20, 2021
A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patientsFederico Calesella, Alberto Testolin, Michele De Filippo De Grazia, et al.
Drug and Alcohol Dependence|May 9, 2021
Investigating predictive factors of dialectical behavior therapy skills training efficacy for alcohol and concurrent substance use disorders: A machine learning studyMarco Cavicchioli, Federico Calesella, Silvia Cazzetta, et al.
Journal of Psychiatric Research|February 17, 2024
Adverse childhood experiences differently affect Theory of Mind brain networks in schizophrenia and healthy controlsBenedetta Vai, Federico Calesella, Alice Pelucchi, et al.
Journal of Psychiatric Research|June 9, 2021
Circulating inflammatory markers impact cognitive functions in bipolar depressionSara Poletti, Mario Gennaio Mazza, Federico Calesella, et al.
Bipolar Disorders|November 15, 2022
Insulin resistance disrupts white matter microstructure and amplitude of functional spontaneous activity in bipolar disorderElena Mazza, Federico Calesella, Marco Paolini, et al.
Human Brain Mapping|December 20, 2024
Assessment of ComBat Harmonization Performance on Structural Magnetic Resonance Imaging MeasurementsEmma Tassi, Anna Maria Bianchi, Federico Calesella, et al.
Neuroscience and Biobehavioral Reviews|February 5, 2022
Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysisFederica Colombo, Federico Calesella, Mario Gennaro Mazza, et al.
Cytokine|December 19, 2024
Circulating inflammatory markers predict depressive symptomatology in COVID-19 survivorsMariagrazia Palladini, Mario Gennaro Mazza, Rebecca De Lorenzo, et al.
Progress in Neuro-Psychopharmacology & Biological Psychiatry|October 12, 2020
A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approachSara Poletti, Benedetta Vai, Mario Gennaro Mazza, et al.
Psychiatry Research. Neuroimaging|March 16, 2023
Reduced corticolimbic habituation to negative stimuli characterizes bipolar depressed suicide attemptersBenedetta Vai, Federico Calesella, Claudia Lenti, et al.
Pageof 3

Showing results (1-10 of 24) with videos related to

Sort By:
Pageof 3
Brain Informatics|April 20, 2021
A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patientsFederico Calesella, Alberto Testolin, Michele De Filippo De Grazia, et al.
Drug and Alcohol Dependence|May 9, 2021
Investigating predictive factors of dialectical behavior therapy skills training efficacy for alcohol and concurrent substance use disorders: A machine learning studyMarco Cavicchioli, Federico Calesella, Silvia Cazzetta, et al.
Journal of Psychiatric Research|February 17, 2024
Adverse childhood experiences differently affect Theory of Mind brain networks in schizophrenia and healthy controlsBenedetta Vai, Federico Calesella, Alice Pelucchi, et al.
Journal of Psychiatric Research|June 9, 2021
Circulating inflammatory markers impact cognitive functions in bipolar depressionSara Poletti, Mario Gennaio Mazza, Federico Calesella, et al.
Bipolar Disorders|November 15, 2022
Insulin resistance disrupts white matter microstructure and amplitude of functional spontaneous activity in bipolar disorderElena Mazza, Federico Calesella, Marco Paolini, et al.
Human Brain Mapping|December 20, 2024
Assessment of ComBat Harmonization Performance on Structural Magnetic Resonance Imaging MeasurementsEmma Tassi, Anna Maria Bianchi, Federico Calesella, et al.
Neuroscience and Biobehavioral Reviews|February 5, 2022
Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysisFederica Colombo, Federico Calesella, Mario Gennaro Mazza, et al.
Cytokine|December 19, 2024
Circulating inflammatory markers predict depressive symptomatology in COVID-19 survivorsMariagrazia Palladini, Mario Gennaro Mazza, Rebecca De Lorenzo, et al.
Progress in Neuro-Psychopharmacology & Biological Psychiatry|October 12, 2020
A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approachSara Poletti, Benedetta Vai, Mario Gennaro Mazza, et al.
Psychiatry Research. Neuroimaging|March 16, 2023
Reduced corticolimbic habituation to negative stimuli characterizes bipolar depressed suicide attemptersBenedetta Vai, Federico Calesella, Claudia Lenti, et al.
Pageof 3