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Kavuluru, Ramakanth

0000-0003-1238-9378

Mayo Clinic

University of Kentucky

Citations 2

An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)
Liu, Sijia , Wen, Andrew , Wang, Liwei , Fu, Sunyang , Miller, Robert , Williams, Andrew E. , Harris, Daniel R. , Liu, Mei , Abu-el-rub, Noor , Schutte, Dalton, Zhang, Rui , Osborne, John D. , He, Yongqun , Topaloĝlu, Ümit , Hong, Stephanie , Schaffter, Thomas , Fuentes, Rafael , Xu, Hua , He, Huan , Fu, Sunyang , Williams, Andrew , Harris, Daniel , Kavuluru, Ramakanth , Liu, Mei , Zhang, Rui , Rouhizadeh, Masoud , Osborne, John D , He, Yongqun , Topaloglu, Umit , Saltz, Joel H , Schaffter, Thomas , Pfaff, Emily , Chute, Christopher G , Haendel, Melissa , Szolovits, Peter , Xu, Hua , Liu, Hongfang , Liu, Sijia , Wen, Andrew , Abu-El-Rub, Noor , He, Huan , Saltz, Joel , Chute, Christopher G. , Duong, Timothy Q. , Haendel, Melissa , Liu, Hongfang

Journal of the American Medical Informatics Association | August 8, 2023 | Volume: 30 | Issue: 12 | Pages: 2036-2040

10.1093/jamia/ocad134 Get It

Abstract Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.
Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine
Islamaj, Rezarta , Kim, Sun , Chatr‐aryamontri, Andrew , Wei, Chih-Hsuan , Comeau, Donald C. , Antunes, Rui , Matos, Sérgio , Chen, Qingyu , Elangovan, Aparna , Panyam, Nagesh C., Verspoor, Karin , Wang, Yanshan , Liu, Zhuang , Altınel, Berna, Hüsünbeyi, Zehra Melce , Özgür, Arzucan , Fergadis, Aris, Wang, Chen-Kai , Dai, Hong-Jie , Tran, Tung , Luo, Ling , Steppi, Albert , Qu, Jinchan, Lu, Zhiyong , Liu, Hongfang , Girgin, Ayşe Berna Altınel , Kavuluru, Ramakanth , Zhang, Jinfeng , Wang, Yanshan

Database | December 21, 2018 | Volume: 2019 | Issue: No issue available | Pages: No page available

10.1093/database/bay147 Get It