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DTSTAMP:20231218T153118Z
UID:F4109E29-0022-4936-8062-2E3DE8BA44B0
DTSTART;TZID=Europe/Rome:20231218T110000
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DESCRIPTION:Recent years have seen a proliferation of commercial platforms 
 designed to automatically assess structural damage in magnetic resonance i
 maging (MRI) of the brain of neurodegenerative patients. These platforms m
 ake extensive use of artificial intelligence (AI) methods to make the asse
 ssment of pathological structural deviations in the brain faster and more 
 accurate. In this presentation\, we will discuss the different areas where
  AI can be used in this context\, highlighting SIENA Imaging approaches an
 d results.\n\nIn detail\, we will discuss some AI applications that we hav
 e recently developed and are implementing in our platform. We will bring e
 xamples of Deep Learning (DL) tools for the segmentation of MRI structures
  (thalamus\, hippocampus and brain volumes)\, and of the use of machine le
 arning (ML) and DL networks for clinical activity prediction and patient c
 lassification. The last part of the talk will be devoted to examining the 
 issues involved in implementing these solutions in a platform and the nume
 rous benefits this implementation could bring. The cons will focus on expl
 aining the technical and bureaucratic aspects. The pros will instead focus
  on the new avenues that AI methods could open up\, and are already openin
 g up\, in the monitoring of neurological diseases.\n\nSpeaker(s): Dr. Marc
 o Battaglini\n\nViale dell'Università\, 50\, Cesena\, Emilia-Romagna\, It
 aly\, Virtual: https://events.vtools.ieee.org/m/391731
LOCATION:Viale dell'Università\, 50\, Cesena\, Emilia-Romagna\, Italy\, Vi
 rtual: https://events.vtools.ieee.org/m/391731
ORGANIZER:s.cangini@unibo.it
SEQUENCE:38
SUMMARY:Use of AI in Neuroimaging: integration in platforms designed for mo
 nitoring Neurological Patients\, pros and cons
URL;VALUE=URI:https://events.vtools.ieee.org/m/391731
X-ALT-DESC:Description: <br /><p>Recent years have seen a proliferation of 
 commercial platforms designed to automatically assess structural damage in
  magnetic resonance imaging (MRI) of the brain of neurodegenerative patien
 ts. These platforms make extensive use of artificial intelligence (AI) met
 hods to make the assessment of pathological structural deviations in the b
 rain faster and more accurate. In this presentation\, we will discuss the 
 different areas where AI can be used in this context\, highlighting SIENA 
 Imaging approaches and results.</p>\n<p>In detail\, we will discuss some A
 I applications that we have recently developed and are implementing in our
  platform. We will bring examples of Deep Learning (DL) tools for the segm
 entation of MRI structures (thalamus\, hippocampus and brain volumes)\, an
 d of the use of machine learning (ML) and DL networks for clinical activit
 y prediction and patient classification.&nbsp\; The last part of the talk 
 will be devoted to examining the issues involved in implementing these sol
 utions in a platform and the numerous benefits this implementation could b
 ring. The cons will focus on explaining the technical and bureaucratic asp
 ects. The pros will instead focus on the new avenues that AI methods could
  open up\, and are already opening up\, in the monitoring of neurological 
 diseases.</p>
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