papers

Publications (10)

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.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.LG2022

Customizing Knowledge Graph Embedding to Improve Clinical Study Recommendation

Xiong Liu, Iya Khalil, Murthy Devarakonda

Inferring knowledge from clinical trials using knowledge graph embedding is an emerging area. However, customizing graph embeddings for different use cases remains a significant ch…

q-bio.GN2024

sc-OTGM: Single-Cell Perturbation Modeling by Solving Optimal Mass Transport on the Manifold of Gaussian Mixtures

Andac Demir, Elizaveta Solovyeva, James Boylan +6

Influenced by breakthroughs in LLMs, single-cell foundation models are emerging. While these models show successful performance in cell type clustering, phenotype classification, a…

cs.IR2021

COVID-19: Comparative Analysis of Methods for Identifying Articles Related to Therapeutics and Vaccines without Using Labeled Data

Mihir Parmar, Ashwin Karthik Ambalavanan, Hong Guan +3

Here we proposed an approach to analyze text classification methods based on the presence or absence of task-specific terms (and their synonyms) in the text. We applied this approa…

cs.CL2020

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.CL2020

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.CL2021

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…

q-bio.QM2021

Clinical Trial Information Extraction with BERT

Xiong Liu, Greg L. Hersch, Iya Khalil +1

Natural language processing (NLP) of clinical trial documents can be useful in new trial design. Here we identify entity types relevant to clinical trial design and propose a frame…

cs.CL2019

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…