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 based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs).
 
Jisang Yu
No Relationships to Disclose
 
Yury Velichko
No Relationships to Disclose
 
Hyeonseon Kim
No Relationships to Disclose
 
Nicolò Gennaro
No Relationships to Disclose
 
Moataz Soliman
No Relationships to Disclose
 
Leeseul Kim
No Relationships to Disclose
 
Youjin Oh
No Relationships to Disclose
 
Trie Arni Djunadi
No Relationships to Disclose
 
Jeeyeon Lee
No Relationships to Disclose
 
Liam Il-Young Chung
No Relationships to Disclose
 
Sung Mi Yoon
No Relationships to Disclose
 
Zunairah Shah
No Relationships to Disclose
 
Won Jun Yang
No Relationships to Disclose
 
Hye Sung Kim
No Relationships to Disclose
 
Yunjoo Lee
No Relationships to Disclose
 
Soowon Lee
No Relationships to Disclose
 
Daeun Kang
No Relationships to Disclose
 
Rishi Agrawal
Speakers' Bureau - Boehringer Ingelheim
 
Pascale Aouad
No Relationships to Disclose
 
Young Kwang Chae
Consulting or Advisory Role - AstraZeneca; Biodesix; Boehringer Ingelheim; Foundation Medicine; Guardant Health; Immuneoncia; Lilly; Lunit; Roche/Genentech; Takeda; Tempus
Speakers' Bureau - AstraZeneca; BMS; G1 Therapeutics; Genentech/Roche; Jazz Pharmaceuticals; Lilly; Merck
Research Funding - Abbvie; Biodesix; Bristol-Myers Squibb; Freenome; Lexent Bio