Multi-omics Investigation on the Prognostic and Predictive Factors in Metastatic Breast Cancer Using Data from Phase III Ribociclib Clinical Trials: A Statistical and Machine Learning Analysis Plan Thibaud Coroller , Berkman Sahiner , Anup Amatya , Alexej Gossmann , Konstantinos Karagiannis , Ravi K. Samala , Luis Santana-Quintero , Nadia Solovieff , Craig Wang , Laleh Amiri-Kordestani , Qian Cao , Kenny H. Cha , Rosane Charlab Orbach , Frank H. Cross , Tingting Hu , Ruihao Huang , Jeffrey Kraft , Peter Krusche , Yutong Li , Zheng Li , Ilya Mazo , Conor Moloney , Rahul Paul , Jason Plawinski , Susan Schnakenberg , Paolo Serra , Sean Smith , Chi Song , Fei Su , Sajanth Subramaniam , Mohit Tiwari , Colin Vechery , Xin Xiong , Juan Pablo Zarate , Jonathan Ziegler , Hao Zhu , Arunava Chakravartty , Qi Liu , David Ohlssen , Nicholas Petrick , Julie A. Schneider , Mark Walderhaug , Emmanuel Zuber openalex（2023）
Key words
Metastatic Breast Cancer, Cancer Genomics, Tumor Heterogeneity, Predictive Modeling
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
