Kristen A. Severson

According to our database, Kristen A. Severson authored at least 15 papers between 2015 and 2023.

Collaborative distances:

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

2023

Considerations for data acquisition and modeling strategies: Mitosis detection in computational pathology.

Zongliang Ji, Philip Rosenfield, Christina Eng, Sarah Bettigole, Danielle C. Gibson, Hamid Masoudi, Matthew Hanna, Nicolò Fusi, Kristen A. Severson

Proceedings of the Medical Imaging with Deep Learning, 2023

2022

Feature Selection Based on Subpopulations and Propensity Score Matching: A Coronary Artery Disease Use Case using the UK Biobank.

Uri Kartoun, Paul Myers, Kristen A. Severson, Wangzhi Dai, Kenney Ng, Collin M. Stultz

Proceedings of the AMIA 2022, 2022

2021

DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways.

Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng

IEEE Trans. Vis. Comput. Graph., 2021

Statistical learning for accurate and interpretable battery lifetime prediction.

Peter M. Attia, Kristen A. Severson, Jeremy D. Witmer

CoRR, 2021

2020

BEEP: A Python library for Battery Evaluation and Early Prediction.

Patrick K. Herring, Chirranjeevi Balaji Gopal, Muratahan Aykol, Joseph Montoya, Abraham Anapolsky, Peter M. Attia, William Gent, Jens S. Hummelshøj, Linda Hung, Ha-Kyung Kwon, Patrick Moore, Daniel Schweigert, Kristen A. Severson, Santosh Suram, Zi Yang, Richard D. Braatz, Brian D. Storey

SoftwareX, 2020

Identifying unreliable predictions in clinical risk models.

Paul Myers, Kenney Ng, Kristen A. Severson, Uri Kartoun, Wangzhi Dai, Wei Huang, Fred Anderson, Collin M. Stultz

npj Digit. Medicine, 2020

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz, Stefano Ermon, William C. Chueh

Nat., 2020

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling.

Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh

Proceedings of the Machine Learning for Healthcare Conference, 2020

2019

DPVis: Visual Exploration of Disease Progression Pathways.

Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng

CoRR, 2019

Generative Oversampling with a Contrastive Variational Autoencoder.

Wangzhi Dai, Kenney Ng, Kristen A. Severson, Wei Huang, Fred Anderson, Collin M. Stultz

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Unsupervised Learning with Contrastive Latent Variable Models.

Kristen A. Severson, Soumya Ghosh, Kenney Ng

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Challenges and opportunities in biopharmaceutical manufacturing control.

Moo Sun Hong, Kristen A. Severson, Mo Jiang, Amos E. Lu, J. Christopher Love, Richard D. Braatz

Comput. Chem. Eng., 2018

2017

A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets.

Kristen A. Severson, Brinda Monian, J. Christopher Love, Richard D. Braatz

Bioinform., 2017

2016

Perspectives on process monitoring of industrial systems.

Kristen A. Severson, Paphonwit Chaiwatanodom, Richard D. Braatz

Annu. Rev. Control., 2016

2015

Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities.

Kristen A. Severson, Jeremy G. VanAntwerp, Venkatesh Natarajan, Chris Antoniou, Jörg Thömmes, Richard D. Braatz

Comput. Chem. Eng., 2015