John Laurentiev - researchr alias

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Viewing Publication 1 - 9 from 9

2025

CD-Tron: Leveraging large clinical language model for early detection of cognitive decline from electronic health recordsHao Guan, John Laurentiev, Li Zhou. jbi, 166:104830, 2025. [doi]

Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health recordsLiqin Wang, John Laurentiev, Claire Cook, Shruthi Srivatsan, Yining Hua, Jie Yang, Eli Miloslavsky, Hyon K. Choi, Li Zhou, Zachary S. Wallace. ijmi, 196:105797, 2025. [doi]

2024

Assessing fairness in machine learning models: A study of racial bias using matched counterparts in mortality prediction for patients with chronic diseasesYifei Wang, Liqin Wang, Zhengyang Zhou, John Laurentiev, Joshua R. Lakin, Li Zhou 0007, Pengyu Hong. jbi, 156:104677, 2024. [doi]

2022

Evaluation of a Machine Learning Approach to Identify ADL Impairment in Clinical Notes of People with DementiaJohn Laurentiev, Mufaddal Mahesri, Lily Bessette, Cassandra York, Heidi Zakoul, Su Been Lee, Dae-Hyun Kim, Li Zhou, Joshua Lin. amia 2022: [doi]

Development and Validation of an Extraction Tool for Identifying Signs and Symptoms of Venous Thromboembolism in Primary Care Clinical NotesJohn Laurentiev, Avery Pullman, Wenyu Song, Ania Syrowatka, Michael Sainlaire, Frank Yu Chang, Luwei Liu, Li Zhou, Patricia C. Dykes. amia 2022: [doi]

Leveraging Big Data and NLP to Understand Patient Care Trajectories and Delayed Diagnosis of Venous Thromboembolism in Primary CareAnia Syrowatka, Lipika Samal, John Laurentiev, Luwei Liu, Azza Omer, Wenyu Song, Michael Sainlaire, Frank Yu Chang, Tien Thai, Li Zhou 0007, David Bates, Patricia C. Dykes. amia 2022: [doi]

2021

1998

Exploiting Enterprise JavaBeans in the NIIIP virtual enterpriseArt Goldschmidt, Paul Horstmann, John Laurentiev. edoc 1998: 124-135 [doi]

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