Automated real-world data integration improves cancer outcome prediction.
Jee J, Fong C, Pichotta K, Tran TN, Luthra A, Waters M, Fu C, Altoe M, Liu SY, Maron SB, Ahmed M, Kim S, Pirun M, Chatila WK, de Bruijn I, Pasha A, Kundra R, Gross B, Mastrogiacomo B, Aprati TJ, Liu D, Gao J, Capelletti M, Pekala K, Loudon L, Perry M, Bandlamudi C, Donoghue M, Satravada BA, Martin A, Shen R, Chen Y, Brannon AR, Chang J, Braunstein L, Li A, Safonov A, Stonestrom A, Sanchez-Vela P, Wilhelm C, Robson M, Scher H, Ladanyi M, Reis-Filho JS, Solit DB, Jones DR, Gomez D, Yu H, Chakravarty D, Yaeger R, Abida W, Park W, O'Reilly EM, Garcia-Aguilar J, Socci N, Sanchez-Vega F, Carrot-Zhang J, Stetson PD, Levine R, Rudin CM, Berger MF, Shah SP, Schrag D, Razavi P, Kehl KL, Li BT, Riely GJ, Schultz N; MSK Cancer Data Science Initiative Group.
Jee J, et al. Among authors: riely gj.
Nature. 2024 Nov 6. doi: 10.1038/s41586-024-08167-5. Online ahead of print.
Nature. 2024.
PMID: 39506116