12 citations · 26 across the 11 of their papers we have counts for
7 papers · 1 filter
A Scalable AI Approach for Clinical Trial Cohort Optimization
Xiong Liu, Cheng Shi, Uday Deore +4
FDA has been promoting enrollment practices that could enhance the diversity of clinical trial populations, through broadening eligibility criteria. However, how to broaden eligibi…
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…
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…
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…
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…
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…