BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Protac - ECPv6.7.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Protac
X-ORIGINAL-URL:https://drugdiscoverypro.com
X-WR-CALDESC:Events for Protac
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20230101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20231118T180000
DTEND;TZID=UTC:20231118T190000
DTSTAMP:20260423T114104
CREATED:20230730T130756Z
LAST-MODIFIED:20230730T131612Z
UID:4208-1700330400-1700334000@drugdiscoverypro.com
SUMMARY:Machine Learning for drug development and deployment
DESCRIPTION:Machine Learning for drug development and deployment Agenda:Machine learning vs deep learning in drug discovery.\n\nFlow chart of model generation for prediction of molecular bioactivity.\n\nIs the Efficiency of the model conditional to the data quality or coding potential?
URL:https://drugdiscoverypro.com/event/machine-learning-for-drug-development-and-deployment/
ATTACH;FMTTYPE=image/jpeg:https://drugdiscoverypro.com/wp-content/uploads/2023/07/product-11.jpg
END:VEVENT
END:VCALENDAR