Urmila Chandran

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 8

Top Topics

Rheumatoid Arthritis

Clinical Decision Support

Ankylosing Spondylitis

Machine Learning

Top Venues

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

This page only lists publications with an associated author ORCID identifier.

Publications

Kyeryoung Lee, Zongzhi Z Liu, Urmila Chandran, Iftekhar Kalsekar, Balaji Laxmanan, Mitchell K Higashi, Tomi Jun, Meng Ma, Minghao Li, Yun Mai, Christopher Gilman, Tongyu Wang, Lei Ai, Parag Aggarwal, Qi Pan, William K Oh, Gustavo Stolovitzky, Eric E Schadt, Xiaoyan Wang
Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning-Based Natural Language Processing. JMIR AI 2 (2023)
Urmila Chandran, Jenna Marie Reps, Robert Yang, Anil Vachani, Fabien Maldonado, Iftekhar Kalsekar
Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 32 (3) (2023)
Urmila Chandran, Jenna Marie Reps, Robert Yang, Anil Vachani, Fabien Maldonado, Iftekhar Kalsekar
Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 32 (3) (2023)
Urmila Chandran, Jenna Marie Reps, Robert Yang, Anil Vachani, Fabien Maldonado, Iftekhar Kalsekar
Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 32 (3) (2023)
Kyeryoung Lee, Zongzhi Z Liu, Urmila Chandran, Iftekhar Kalsekar, Balaji Laxmanan, Mitchell K Higashi, Tomi Jun, Meng Ma, Minghao Li, Yun Mai, Christopher Gilman, Tongyu Wang, Lei Ai, Parag Aggarwal, Qi Pan, William K Oh, Gustavo Stolovitzky, Eric E Schadt, Xiaoyan Wang
Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning-Based Natural Language Processing. JMIR AI 2 (2023)
Kyeryoung Lee, Zongzhi Z Liu, Urmila Chandran, Iftekhar Kalsekar, Balaji Laxmanan, Mitchell K Higashi, Tomi Jun, Meng Ma, Minghao Li, Yun Mai, Christopher Gilman, Tongyu Wang, Lei Ai, Parag Aggarwal, Qi Pan, William K Oh, Gustavo Stolovitzky, Eric E Schadt, Xiaoyan Wang
Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning-Based Natural Language Processing. JMIR AI 2 (2023)
Urmila Chandran, Jenna Marie Reps, Robert Yang, Anil Vachani, Fabien Maldonado, Iftekhar Kalsekar
Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (2022)
Urmila Chandran, Jenna Reps, Paul E Stang, Patrick B Ryan
Inferring disease severity in rheumatoid arthritis using predictive modeling in administrative claims databases. PloS one 14 (12) (2019)