The following represents disclosure information provided by authors of this abstract. The program committee has reviewed all presenting author disclosure reports, identified potential conflicts of interest, and implemented strategies to manage those areas of conflict, where appropriate. All relationships are considered compensated. Relationships are self-held unless otherwise noted. I = Immediate Family Member, Inst = My Institution
 
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Machine learning models to predict the response to anti-cancer therapy in metastatic melanoma patients.
 
Romain Goussault
Consulting or Advisory Role - Owkin
 
Cécile Frénard
No Relationships to Disclose
 
Eve Maubec
Consulting or Advisory Role - Bristol-Myers Squibb; MSD; Pierre Fabre
Research Funding - MSD (Inst)
Travel, Accommodations, Expenses - MSD Oncology; Pierre Fabre; Pierre Fabre
(OPTIONAL) Uncompensated Relationships - MSD Oncology
 
Philippe Muller
No Relationships to Disclose
 
Ludovic Martin
No Relationships to Disclose
 
Delphine Legoupil
No Relationships to Disclose
 
Francois Aubin
No Relationships to Disclose
 
Julie De Quatrebarbes
Speakers' Bureau - Bristol-Myers Squibb; Janssen-Cilag
Travel, Accommodations, Expenses - BMS Brazil; MSD Oncology
 
Thomas Jouary
No Relationships to Disclose
 
Alice Hervieu
No Relationships to Disclose
 
Laurent Machet
No Relationships to Disclose
 
Emilie Varey
No Relationships to Disclose
 
Philippe Lecerf
No Relationships to Disclose
 
Florence Vrignaud
No Relationships to Disclose
 
Amir Khammari
Travel, Accommodations, Expenses - Bristol-Myers Squibb; Roche/Genentech
 
Brigitte Dréno
Consulting or Advisory Role - Bristol-Myers Squibb; Pierre Fabre; Roche/Genentech
Research Funding - Bristol-Myers Squibb (Inst); Roche (Inst)
Travel, Accommodations, Expenses - Bristol-Myers Squibb; Roche/Genentech