activity
20182020
most citedLATTE: Latent Type Modeling for Biomedical Entity Linking

4 citations · 7 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL2020

Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network

Shaoqing Yuan, Parminder Bhatia, Busra Celikkaya +2

Recent advancements in medical entity linking have been applied in the area of scientific literature and social media data. However, with the adoption of telemedicine and conversat…

cs.CL20194 cited

LATTE: Latent Type Modeling for Biomedical Entity Linking

Ming Zhu, Busra Celikkaya, Parminder Bhatia +1

Entity linking is the task of linking mentions of named entities in natural language text, to entities in a curated knowledge-base. This is of significant importance in the biomedi…

cs.CL20193 cited

Comprehend Medical: a Named Entity Recognition and Relationship Extraction Web Service

Parminder Bhatia, Busra Celikkaya, Mohammed Khalilia +1

Comprehend Medical is a stateless and Health Insurance Portability and Accountability Act (HIPAA) eligible Named Entity Recognition (NER) and Relationship Extraction (RE) service l…

cs.CL2018

Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning

Mengqi Jin, Mohammad Taha Bahadori, Aaron Colak +11

Clinical text provides essential information to estimate the acuity of a patient during hospital stays in addition to structured clinical data. In this study, we explore how clinic…

cs.LG2018

Dynamic Transfer Learning for Named Entity Recognition

Parminder Bhatia, Kristjan Arumae, Busra Celikkaya

State-of-the-art named entity recognition (NER) systems have been improving continuously using neural architectures over the past several years. However, many tasks including NER r…

cs.CL2018

Joint Entity Extraction and Assertion Detection for Clinical Text

Parminder Bhatia, Busra Celikkaya, Mohammed Khalilia

Negative medical findings are prevalent in clinical reports, yet discriminating them from positive findings remains a challenging task for information extraction. Most of the exist…