Case Study
Centralized Streamlining of Data Curation to Accelerate COVID-19 AI Research at the University of Wisconsin
Centralized Streamlining of Data Curation to Accelerate COVID-19 AI Research at the University of Wisconsin
C e n t r a l i z e d S t r e a m l i n i n g o f D a t a C u r a t i o n t o A c c e l e r a t e C O V I D - 1 9 A I R e s e a r c h a t t h e U n i v e r s i t y o f W i s c o n s i n R ecent dev elopments in medical imaging-based deep learning models pr o vide r adiologists a new set of biomark ers to diagnose associated diseases such as CO VID-19 based pneumonia. T o dev elop accur ate deep learning models, ho w ev er , or ganizations need access to po w er ful computing r esour ces and a high v olume of medical images and associated data that has been cur ated to common standar ds and assessed f or quality . AI infr astructur e is essential f or cr eating unbiased data sets and algorithms, all while pr otecting clinical priv acy and maintaining r egulator y compliance. Dr .