211 citations · 289 across the 15 of their papers we have counts for
16 papers
Towards Answering Health-related Questions from Medical Videos: Datasets and Approaches
Deepak Gupta, Kush Attal, Dina Demner-Fushman
The increase in the availability of online videos has transformed the way we access information and knowledge. A growing number of individuals now prefer instructional videos as th…
Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking
Deepak Gupta, Dina Demner-Fushman
Pre-trained language models (PLMs) have proven to be effective for document re-ranking task. However, they lack the ability to fully interpret the semantics of biomedical and healt…
A Dataset for Plain Language Adaptation of Biomedical Abstracts
Kush Attal, Brian Ondov, Dina Demner-Fushman
Though exponentially growing health-related literature has been made available to a broad audience online, the language of scientific articles can be difficult for the general publ…
Medical Image Retrieval via Nearest Neighbor Search on Pre-trained Image Features
Deepak Gupta, Russell Loane, Soumya Gayen +1
Nearest neighbor search (NNS) aims to locate the points in high-dimensional space that is closest to the query point. The brute-force approach for finding the nearest neighbor beco…
Clinical Language Understanding Evaluation (CLUE)
Travis R. Goodwin, Dina Demner-Fushman
Clinical language processing has received a lot of attention in recent years, resulting in new models or methods for disease phenotyping, mortality prediction, and other tasks. Unf…
CHQ-Summ: A Dataset for Consumer Healthcare Question Summarization
Shweta Yadav, Deepak Gupta, Dina Demner-Fushman
The quest for seeking health information has swamped the web with consumers' health-related questions. Generally, consumers use overly descriptive and peripheral information to exp…
A Dataset for Medical Instructional Video Classification and Question Answering
Deepak Gupta, Kush Attal, Dina Demner-Fushman
This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language que…
Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards
Shweta Yadav, Deepak Gupta, Asma Ben Abacha +1
The growth of online consumer health questions has led to the necessity for reliable and accurate question answering systems. A recent study showed that manual summarization of con…
Question-aware Transformer Models for Consumer Health Question Summarization
Shweta Yadav, Deepak Gupta, Asma Ben Abacha +1
Searching for health information online is becoming customary for more and more consumers every day, which makes the need for efficient and reliable question answering systems more…
Searching for Scientific Evidence in a Pandemic: An Overview of TREC-COVID
Kirk Roberts, Tasmeer Alam, Steven Bedrick +6
We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COV…
Question-Driven Summarization of Answers to Consumer Health Questions
Max Savery, Asma Ben Abacha, Soumya Gayen +1
Automatic summarization of natural language is a widely studied area in computer science, one that is broadly applicable to anyone who routinely needs to understand large quantitie…
TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick +6
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pand…
Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge
Travis R. Goodwin, Dina Demner-Fushman
In this paper we present OSCAR (Ontology-based Semantic Composition Augmented Regularization), a method for injecting task-agnostic knowledge from an Ontology or knowledge graph in…
Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning
Surabhi Datta, Yuqi Si, Laritza Rodriguez +3
We define a representation framework for extracting spatial information from radiology reports (Rad-SpRL). We annotated a total of 2000 chest X-ray reports with 4 spatial roles cor…
A Question-Entailment Approach to Question Answering
Asma Ben Abacha, Dina Demner-Fushman
One of the challenges in large-scale information retrieval (IR) is to develop fine-grained and domain-specific methods to answer natural language questions. Despite the availabilit…
Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation
Hoo-Chang Shin, Kirk Roberts, Le Lu +3
Despite the recent advances in automatically describing image contents, their applications have been mostly limited to image caption datasets containing natural images (e.g., Flick…