MALESANI, MICHELE

	Nome completo
	
					MALESANI, MICHELE
				
	Afferenza
	
					Dipartimento Universitario Clinico di Scienze mediche, chirurgiche e della salute
				
	Tipo di ruolo
	
					Specializzandi

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Atrial fibrillation detected after ischemic stroke (AFDAS) diagnosed by short-term monitoring: the importance of frontal hypoperfusion

2026-01-01 Prandin, Gabriele; Furlanis, Giovanni; Mancinelli, Laura; Vincis, Emanuele; Quagliotto, Magda; Ricci, Edoardo; Malesani, Michele; Farina, Gianpiero; Cattaruzza, Luigi; Caruso, Paola; Naccarato, Marcello; Ukmar, Maja; Manganotti, Paolo

Interictal epileptiform activity in the acute stroke phase: an independent predictor of poor outcome

2026-01-01 Furlanis, Giovanni; Iscra, Katerina; Ricci, Edoardo; Malesani, Michele; Prandin, Gabriele; Vincis, Emanuele; Mancinelli, Laura; Palacino, Federica; Quagliotto, Magda; Caruso, Paola; Naccarato, Marcello; Ajčević, Miloš; Manganotti, Paolo

Optimizing machine learning models for classification of stroke patients with epileptiform EEG pattern: the impact of dataset balancing techniques

2024-01-01 Iscra, Katerina; Biscontin, Alessandro; Miladinovic, Aleksandar; Bonini, Andrea; Furlanis, Giovanni; Prandin, Gabriele; Malesani, Michele; Naccarato, Marcello; Manganotti, Paolo; Accardo, Agostino; Ajčević, Miloš

Titolo	Data di pubblicazione	Autori
Atrial fibrillation detected after ischemic stroke (AFDAS) diagnosed by short-term monitoring: the importance of frontal hypoperfusion	1-gen-2026	Prandin, GabrieleFurlanis, GiovanniMancinelli, LauraVincis, EmanueleQuagliotto, MagdaRicci, EdoardoMalesani, MicheleFarina, GianpieroCattaruzza, LuigiCaruso, PaolaNaccarato, MarcelloUkmar, MajaManganotti, Paolo + -
Interictal epileptiform activity in the acute stroke phase: an independent predictor of poor outcome	1-gen-2026	Furlanis, GiovanniIscra, KaterinaRicci, EdoardoMalesani, MichelePrandin, GabrieleVincis, EmanueleMancinelli, LauraPalacino, FedericaQuagliotto, MagdaCaruso, PaolaNaccarato, MarcelloAjčević, MilošManganotti, Paolo + -
Optimizing machine learning models for classification of stroke patients with epileptiform EEG pattern: the impact of dataset balancing techniques	1-gen-2024	Iscra, KaterinaBiscontin, AlessandroMiladinovic, AleksandarBonini, AndreaFurlanis, GiovanniPrandin, GabrieleMalesani, MicheleNaccarato, MarcelloManganotti, PaoloAccardo, AgostinoAjčević, Miloš + -

ArTS Archivio della ricerca di Trieste

MALESANI, MICHELE

Atrial fibrillation detected after ischemic stroke (AFDAS) diagnosed by short-term monitoring: the importance of frontal hypoperfusion

Interictal epileptiform activity in the acute stroke phase: an independent predictor of poor outcome

Optimizing machine learning models for classification of stroke patients with epileptiform EEG pattern: the impact of dataset balancing techniques