Search Results for author: Preethi Raghavan

Found 10 papers, 3 papers with code

TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces

1 code implementation1 Jul 2020 So Yeon Min, Preethi Raghavan, Peter Szolovits

We propose TransINT, a novel and interpretable KG embedding method that isomorphically preserves the implication ordering among relations in the embedding space.

Knowledge Graphs Link Prediction +1

Entity-Enriched Neural Models for Clinical Question Answering

2 code implementations WS 2020 Bhanu Pratap Singh Rawat, Wei-Hung Weng, So Yeon Min, Preethi Raghavan, Peter Szolovits

We explore state-of-the-art neural models for question answering on electronic medical records and improve their ability to generalize better on previously unseen (paraphrased) questions at test time.

Question Answering

emrQA: A Large Corpus for Question Answering on Electronic Medical Records

2 code implementations EMNLP 2018 Anusri Pampari, Preethi Raghavan, Jennifer Liang, Jian Peng

We propose a novel methodology to generate domain-specific large-scale question answering (QA) datasets by re-purposing existing annotations for other NLP tasks.

Question Answering

Annotating Electronic Medical Records for Question Answering

no code implementations17 May 2018 Preethi Raghavan, Siddharth Patwardhan, Jennifer J. Liang, Murthy V. Devarakonda

Over the course of 11 months, 11 medical students followed our annotation methodology, resulting in a question answering dataset of 5696 questions over 71 patient records, of which 1747 questions have corresponding answers generated by the medical students.

Question Answering

How essential are unstructured clinical narratives and information fusion to clinical trial recruitment?

no code implementations13 Feb 2015 Preethi Raghavan, James L. Chen, Eric Fosler-Lussier, Albert M. Lai

We perform an empirical study to validate the argument and show that structured data alone is insufficient in resolving eligibility criteria for recruiting patients onto clinical trials for chronic lymphocytic leukemia (CLL) and prostate cancer.

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