BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:The Applied Machine Learning Days – AI & Pharma
DTSTART:20210823T083000
DTEND:20210823T173000
DTSTAMP:20260407T042102Z
UID:1efbf6028d1aba26f9decc4c2b0a33dae4209905aa330b102ece1cef
CATEGORIES:Conferences - Seminars
DESCRIPTION:André Jaun\nCamille Marini\, PhD \nCécile Louwers\nEnkelejd
 a Miho\nJason Plawinski\nJonas Richiardi\nKhaled El Emam\nKostas Sechidis\
 nKurt Stockinger\nLimor Shmerling Magazanik\nLisa Herzog\nPatrick Schwab\n
 Simone Lionetti\nJean-Pierre Hubaux\nThe Applied Machine Learning Days are
  one of the largest machine learning & AI events in Europe\, focused speci
 fically on the applications of machine learning and AI\, making it particu
 larly interesting to industry and academia.\nEach month\, a domain-specifi
 c track will feature top-level speakers\, discussions and keynotes. Some t
 racks will be preceded or followed by a workshop day focussed on hand-on s
 essions\, coding classes and tutorials. \n\nGiven the enormous increase i
 n healthcare data volumes\, our ability to effectively share\, integrate a
 nd analyze is critical to advancing our understanding of the disease and b
 ringing affordable and efficacious treatments to patients. Due to the brea
 dth and depth of the healthcare data across various modalities such as cli
 nical\, genomics\, imaging and digital sensors\, we need to move beyond tr
 aditional methods and bring advanced ML/AI implementations to maximally be
 nefit from the richness of the collected data. As part of the drug develop
 ment life-cycle vast amounts of clinical trials data are collected in orde
 r to identify targets of interest\, discover biomarkers to stratify patien
 ts who could benefit from the drug\, and to study the safety and benefit p
 rofile of the drug. Furthermore\, after the drug is brought to the market 
 its use in a broader population is collected in a wide range of real-world
  data sources including\, but not limited to\, electronic medical records\
 , disease registries\, health insurance claims​\, ​and digital device
 s. To date the Pharma industry has not leveraged the wealth of this inform
 ation to deliver truly personalized care for patients.\nDevelopment of adv
 anced ​statistical and machine learning​ methodologies combined with t
 he availability of scalable computing environments is fueling a new wave o
 f digitization in Pharma R&D pipelines thereby creating possibilities to d
 iscover and develop personalized medicines. This track will invite experts
  from industry and academia to share their experiences in using AI/ML for 
 Pharma R&D to showcase successful implementations and also lay the roadmap
  of future methodological and application innovations accelerating use of 
 ML/AI within Pharma research.\n\nTickets
LOCATION:
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR