BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//datacraft - ECPv6.16.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:datacraft
X-ORIGINAL-URL:https://datacraft.paris
X-WR-CALDESC:Events for datacraft
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20220327T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20221030T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20220624T110000
DTEND;TZID=Europe/Paris:20220624T120000
DTSTAMP:20260514T145429
CREATED:20220524T161948Z
LAST-MODIFIED:20220524T162813Z
UID:6825-1656068400-1656072000@datacraft.paris
SUMMARY:MINDSHAKE TIME - Vision Transformer classification applied to computer vision medical diagnosis
DESCRIPTION:inscription\n			\n				\n				\n				\n				\n				In this workshop\, we will discuss on Vision Transformer classification applied on medical diagnosis. After introducing Transformers and the mechanism of self-attention\, we will show the results of the ViT architecture compared with a classic CNN and a multistage architecture composed of successive CNNs. \nWe will then show how In recent years\, the scientific community focused on developing Computer-Aided Diagnosis tools that could improve clinicians’ bone fracture diagnosis\, primarily based on Convolutional Neural Networks (CNNs). However\, the discerning accuracy of fractures’ subtypes was far from optimal. The aim of this study is to evaluate a new CAD system based on Vision Transformers (ViT) and to assess whether clinicians’ diagnostic accuracy could be improved using this system. \nTo demonstrate this\, we will discuss an evaluation made by 11 clinicians\, who were asked to classify 150 proximal femur fracture images with and without the help of the ViT.  \nWorkshop led by Leonardo Tanzi\, PhD student at Polytechnic University of Turin
URL:https://datacraft.paris/event/mindshake-time-vision-transformer-classification-applied-to-computer-vision-medical-diagnosis/
LOCATION:datacraft –\, 3 rue Rossini\, 75009 Paris\, France
CATEGORIES:- Event in English -
ORGANIZER;CN="datacraft":MAILTO:contact@datacraft.paris
END:VEVENT
END:VCALENDAR