Kristen Severson

According to our database, Kristen Severson authored at least 4 papers between 2022 and 2023.

Collaborative distances:

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

2023

Improving mitosis detection on histopathology images using large vision-language models.

Ruiwen Ding, James Brian Hall, Neil A. Tenenholtz, Kristen Severson

CoRR, 2023

Machine Learning for Health (ML4H) 2023.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen

Proceedings of the Machine Learning for Health, 2023

2022

Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data.

Divya Ramamoorthy, Kristen Severson, Soumya Ghosh, Karen Sachs, Emily G. Baxi, Alyssa N. Coyne, Elizabeth Mosmiller, Lindsey Hayes, Aianna Cerezo, Omar Ahmad, Promit Roy, Steven Zeiler, John W. Krakauer, Jonathan Li, Aneesh Donde, Nhan Huynh, Miriam Adam, Brook T. Wassie, Alexander LeNail, Natasha Leanna Patel-Murray, Yogindra Raghav, Velina Kozareva, Stanislav Tsitkov, Tobias Ehrenberger, Julia A. Kaye, Leandro Lima, Stacia K. Wyman, Edward Vertudes, Naufa Amirani, Krishna Raja, Reuben Thomas, Ryan G. Lim, Ricardo Miramontes, Jie Wu, Vineet Vaibhav, Andrea Matlock, Vidya Venkatraman, Ronald Holewenski, Niveda Sundararaman, Rakhi Pandey, Danica-Mae Manalo, Aaron Frank, Loren Ornelas, Lindsey Panther, Emilda Gomez, Erick Galvez, Daniel Pérez, Imara Meepe, Susan Lei, Louis Pinedo, Chunyan Liu, Ruby Moran, Dhruv Sareen, Barry Landin, Carla Agurto, Guillermo A. Cecchi, Raquel Norel, Sara Thrower, Sarah Luppino, Alanna Farrar, Lindsay Pothier, Hong Yu, Ervin Sinani, Prasha Vigneswaran, Alexander V. Sherman, S. Michelle Farr, Berhan Mandefro, Hannah Trost, Maria G. Banuelos, Veronica Garcia, Michael Workman, Richie Ho, Robert Baloh, Jennifer Roggenbuck, Matthew B. Harms, Carolyn Prina, Sarah Heintzman, Stephen Kolb, Jennifer Stocksdale, Keona Wang, Todd Morgan, Daragh Heitzman, Arish Jamil, Jennifer Jockel-Balsarotti, Elizabeth Karanja, Jesse Markway, Molly McCallum, Tim Miller, Ben Joslin, Deniz Alibazoglu, Senda Ajroud-Driss, Jay C. Beavers, Mary Bellard, Elizabeth Bruce, Nicholas J. Maragakis, Merit E. Cudkowicz, James D. Berry, Terri Thompson, Steven Finkbeiner, Leslie M. Thompson, Jennifer E. Van Eyk, Clive N. Svendsen, Jeffrey D. Rothstein, Jonathan D. Glass, Christina N. Fournier, Alexander Sherman, Christian Lunetta, David Walk, Ghazala Hayat, James Wymer, Kelly Gwathmey, Nicholas Olney, Terry Heiman-Patterson, Ximena Arcila-Londono, Kenneth Faulconer, Ervin Sanani, Alex Berger, Julia Mirochnick, Todd M. Herrington, Kenney Ng, Ernest Fraenkel

Nat. Comput. Sci., 2022

Machine Learning for Health (ML4H) 2022.

Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi

Proceedings of the Machine Learning for Health, 2022