most citedRobustly Pre-trained Neural Model for Direct Temporal Relation Extraction

5 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Cascade Neural Ensemble for Identifying Scientifically Sound Articles

Ashwin Karthik Ambalavanan, Murthy Devarakonda

Background: A significant barrier to conducting systematic reviews and meta-analysis is efficiently finding scientifically sound relevant articles. Typically, less than 1% of artic…

cs.CL20205 cited

Robustly Pre-trained Neural Model for Direct Temporal Relation Extraction

Hong Guan, Jianfu Li, Hua Xu +1

Background: Identifying relationships between clinical events and temporal expressions is a key challenge in meaningfully analyzing clinical text for use in advanced AI application…

cs.CL2019

Knowledge Guided Named Entity Recognition for BioMedical Text

Pratyay Banerjee, Kuntal Kumar Pal, Murthy Devarakonda +1

In this work, we formulate the NER task as a multi-answer knowledge guided QA task (KGQA) which helps to predict entities only by assigning B, I and O tags without associating enti…

cs.CL2019

Training Models to Extract Treatment Plans from Clinical Notes Using Contents of Sections with Headings

Ananya Poddar, Bharath Dandala, Murthy Devarakonda

Objective: Using natural language processing (NLP) to find sentences that state treatment plans in a clinical note, would automate plan extraction and would further enable their us…

cs.CL20192 cited

Developing and Using Special-Purpose Lexicons for Cohort Selection from Clinical Notes

Samarth Rawal, Ashok Prakash, Soumya Adhya +4

Background and Significance: Selecting cohorts for a clinical trial typically requires costly and time-consuming manual chart reviews resulting in poor participation. To help autom…