Rebecca Rojansky

According to our database, Rebecca Rojansky authored at least 4 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype.

Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar

Proceedings of the Machine Learning for Health, 2023

2021

Biological data annotation via a human-augmenting AI-based labeling system.

Douwe van der Wal, Iny Jhun, Israa Laklouk, Jeffrey J. Nirschl, Lara Richer, Rebecca Rojansky, Talent Theparee, Joshua Wheeler, Jörg Sander, Felix Y. Feng, Osama Mohamad, Silvio Savarese, Richard Socher, Andre Esteva

npj Digit. Medicine, 2021

Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

Grace Y. E. Kim, Morteza Noshad, Henning Stehr, Rebecca Rojansky, Dita Gratzinger, Jean Oak, Rondeep Brar, David Iberri, Christina Kong, James L. Zehnder, Jonathan H. Chen

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set.

Damir Vrabac, Akshay Smit, Rebecca Rojansky, Yasodha Natkunam, Ranjana H. Advani, Andrew Y. Ng, Sebastian Fernandez-Pol, Pranav Rajpurkar

CoRR, 2020