Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology.

Saverio D'Amico Daniele Dall'Olio Claudia Sala Lorenzo Dall'Olio Elisabetta Sauta Matteo Zampini Gianluca Asti Luca LaninoGiulia MaggioniAlessia CampagnaMarta UbezioAntonio Russo Maria Elena Bicchieri Elena RivaCristina A TentoriErica TravaglinoPierandrea MorandiniVictor SavevskiArmando SantoroIñigo Prada-LuengoAnders Krogh Valeria Santini Shahram Kordasti Uwe PlatzbeckerMaria Diez-CampeloPierre FenauxTorsten HaferlachGastone C Castellani Matteo Giovanni Della Porta

Published in: JCO clinical cancer informatics (2023)

Synthetic data mimic real clinical-genomic features and outcomes, and anonymize patient information. The implementation of this technology allows to increase the scientific use and value of real data, thus accelerating precision medicine in hematology and the conduction of clinical trials.

Keyphrases

artificial intelligence
big data
electronic health record
clinical trial
machine learning
primary care
deep learning
healthcare
gene expression
data analysis
health information
quality improvement
metabolic syndrome
phase ii
genome wide
study protocol
placebo controlled