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Griesbeck M, Ziegler S, Laffont S, Smith N, Chauveau L, Tomezsko P, et al

biophysical Res

Disclosure of interest: Stefano Mombelli: nothing to disclose Francesco Arba: nothing to disclose Chiara Rinaldi: nothing to disclose Marialuisa Zedde: nothing to disclose Andrea Morotti: nothing to disclose Andrea Zini: nothing to disclose Stefano Forlivesi: nothing to disclose Chiara Bassi: nothing to disclose Giuseppe Reale: nothing to disclose Rosario Pascarella: nothing to disclose Federico Mazzacane: nothing to disclose Pietro Caliandro: nothing to disclose Aurelia Zauli: nothing to disclose E-Posters - DIAGNOSIS / ETIOLOGY 04.00 - DIAGNOSIS / ETIOLOGY - 04.01 - DIAGNOSIS/INVESTIGATION OF STROKE ETIOLOGY P2390 - ESOC25-1680 LEVERAGING CLINICAL AND ECHOCARDIOGRAPHIC PREDICTORS WITH AI MODELS TO OPTIMIZE TRANSESOPHAGEAL ECHOCARDIOGRAPHY IN ISCHEMIC STROKE PATIENTS Mohiudeen Alikunju 1 , Maria Khan 1 , Mumtaz Ummar 1 1 mohammed bin rashid university, dubai, United Arab Emirates Background and Aims: Transesophageal echocardiography (TEE) uncovers embolic sources often missed by transthoracic echocardiography (TTE), but its exact indications are unclear

Lipidomics, an approach to provide global profiles of lipids, has improved significantly with the advancement of next-generation mass spectrometry instruments, and bioinformatics

Seglen PO