cwarnold@ucla.edu
(310) 794-3538
Office Info

924 Westwood Blvd, Suite 420, Room E

Corey W. Arnold, PhD

Director, Computational Diagnostics (CDx)
Associate Professor, Departments of Radiological Sciences, Pathology & Laboratory Medicine, Bioengineering & Bioinformatics

Biography

Dr. Corey Arnold is an Associate Professor with a joint appointment in the UCLA Departments of Radiological Sciences and Pathology & Laboratory Medicine. He leads the Computational Diagnostics program, a joint effort between the departments. His areas of research include medical image analysis, computational phenotyping, natural language processing, and multi-scale predictive disease modeling, with a preference for problems that have a clear pathway to clinical translation. Most projects share the goal of integrating radiology, pathology, and -omic features to further our understanding of disease through the discovery of predictive computational phenotypes that may be used for risk stratification, treatment selection, and response monitoring. His lab also serves as a resource for department physicians, fellows, and residents who wish to incorporate machine learning/data science techniques into their research.

Publications

2020

Meng Y, Speier W, Ong M, Arnold CW. Multi-level embedding with topic modeling on electronic health records for predicting depression. Proc AAAI Health Intelligence Workshop. New York City, NY. February 7-12, 2020.

2019

Sohn A, Speier W, Lan E, Aoki K, Fonarow G, Ong M, Arnold CW. Assessment of Heart Failure Patients' Interest in Mobile Health Apps for Self-Care: Survey Study. JMIR Cardio. 2019 Oct 29;3(2):e14332. DOI: 10.2196/14332. PMID: 31758788; PMCID: PMC6851712.
Meng Y, Speier W, Shufelt C, Joung S, E Van Eyk J, Bairey Merz CN, Lopez M, Spiegel B, Arnold CW. A Machine Learning Approach to Classifying Self-Reported Health Status in a Cohort of Patients With Heart Disease Using Activity Tracker Data. IEEE J Biomed Health Inform. 2020 Mar;24(3):878-884. DOI: 10.1109/JBHI.2019.2922178. Epub 2019 Jun 11. PMID: 31199276; PMCID: PMC6904535.
Li J, Li W, Gertych A, Knudsen BS, Speier W, Arnold CW. An attention-based multi-resolution model for prostate whole slide image classification and localization. arXiv preprint arXiv:1905.13208. 2019 May 30.
Li W, Wang Z, Yue Y, Li J, Speier W, Zhou M, Arnold CW. Semi-supervised Learning using Adversarial Training with Good and Bad Samples. arXiv preprint arXiv:1910.08540. 2019 Oct 18.

Li W, Wang Z, Li J, Polson J, Speier W, Arnold CW. Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach. arXiv preprint arXiv:1905.06484. 2019 May 16.

2018

Meng Y, Speier W, Dzubur E, Spiegel B, Arnold CW. Predicting Patient Health Status using Activity Tracker Data. Proceedings of the 2018 American Medical Informatics Association Annual Symposium. San Francisco; 2018. PDF
Li W, Wang Y, Cai Y, Arnold CW, Zhao E, Yuan Y. Semi-supervised rare disease detection using generative adversarial network. arXiv preprint arXiv:1812.00547. 2018 Dec 3.
Li J, Speier W, Ho KC, Sarma KV, Gertych A, Knudsen BS, Arnold CW. An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies. Comput Med Imaging Graph. 2018 Nov;69:125-133. DOI: 10.1016/j.compmedimag.2018.08.003. Epub 2018 Sep 3. PMID: 30243216; PMCID: PMC6173982.
Ing N, Ma Z, Li J, Salemi H, Arnold CW, Knudsen BS, Gertych A. Semantic segmentation for prostate cancer grading by convolutional neural networks. Medical Imaging 2018: Digital Pathology. International Society for Optics and Photonics. 2018. p. 105811B.

Research Projects