1 code implementation • 22 May 2024 • Monika Jain, Raghava Mutharaju, Kuldeep Singh, Ramakanth Kavuluru
Relation extraction (RE) is a well-known NLP application often treated as a sentence- or document-level task.
no code implementations • 21 Feb 2024 • Aviv Brokman, Ramakanth Kavuluru
As such, generative LMs pretrained on biomedical corpora have proliferated and biomedical instruction finetuning has been attempted as well, all with the hope that domain specificity improves performance on downstream tasks.
1 code implementation • 22 Jan 2024 • Monika Jain, Raghava Mutharaju, Ramakanth Kavuluru, Kuldeep Singh
Document-level relation extraction (DocRE) poses the challenge of identifying relationships between entities within a document as opposed to the traditional RE setting where a single sentence is input.
1 code implementation • 22 Nov 2023 • Shashank Gupta, Xuguang Ai, Ramakanth Kavuluru
Our contribution is also the first to conduct E2ERE for the RareDis dataset.
no code implementations • 3 Apr 2023 • Xuguang Ai, Ramakanth Kavuluru
End-to-end relation extraction (E2ERE) is an important task in information extraction, more so for biomedicine as scientific literature continues to grow exponentially.
Chemical-Protein Interaction Extraction named-entity-recognition +4
1 code implementation • 29 Mar 2023 • Yuhang Jiang, Ramakanth Kavuluru
Extracting combination therapies from scientific literature inherently constitutes an $n$-ary relation extraction problem.
2 code implementations • 19 Mar 2023 • Yuhang Jiang, Ramakanth Kavuluru
As COVID-19 ravages the world, social media analytics could augment traditional surveys in assessing how the pandemic evolves and capturing consumer chatter that could help healthcare agencies in addressing it.
no code implementations • 25 Feb 2022 • Patrick J. Ward, April M. Young, Svetla Slavova, Madison Liford, Lara Daniels, Ripley Lucas, Ramakanth Kavuluru
Surveillance of drug overdose deaths relies on death certificates for identification of the substances that caused death.
no code implementations • 20 Oct 2021 • Sijia Liu, Andrew Wen, LiWei Wang, Huan He, Sunyang Fu, Robert Miller, Andrew Williams, Daniel Harris, Ramakanth Kavuluru, Mei Liu, Noor Abu-el-rub, Dalton Schutte, Rui Zhang, Masoud Rouhizadeh, John D. Osborne, Yongqun He, Umit Topaloglu, Stephanie S Hong, Joel H Saltz, Thomas Schaffter, Emily Pfaff, Christopher G. Chute, Tim Duong, Melissa A. Haendel, Rafael Fuentes, Peter Szolovits, Hua Xu, Hongfang Liu, Natural Language Processing, Subgroup, National COVID Cohort Collaborative
Although we use COVID-19 as a use case in this effort, our framework is general enough to be applied to other domains of interest in clinical NLP.
no code implementations • 16 Mar 2021 • Sajjad Fouladvand, Jeffery Talbert, Linda P. Dwoskin, Heather Bush, Amy Lynn Meadows, Lars E. Peterson, Ramakanth Kavuluru, Jin Chen
Opioid Use Disorder (OUD) is a public health crisis costing the US billions of dollars annually in healthcare, lost workplace productivity, and crime.
1 code implementation • 22 Dec 2020 • Jiho Noh, Ramakanth Kavuluru
This fine-tuning is accomplished with the BERT transformer architecture in the two-sentence input mode with a classification objective that captures MeSH pair co-occurrence.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Jiho Noh, Ramakanth Kavuluru
Component (a) directly generates a matching score of a candidate document for a query.
no code implementations • 6 Oct 2020 • Gongbo Liang, Connor Greenwell, Yu Zhang, Xiaoqin Wang, Ramakanth Kavuluru, Nathan Jacobs
A key challenge in training neural networks for a given medical imaging task is often the difficulty of obtaining a sufficient number of manually labeled examples.
no code implementations • 28 Oct 2019 • Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
As drug-drug interactions (DDIs) may lead to preventable adverse events, being able to extract DDIs from drug labels into a machine-processable form is an important step toward effective dissemination of drug safety information.
no code implementations • 17 May 2019 • Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels into machine-readable form is an important effort in effectively deploying drug safety information.
no code implementations • 17 May 2019 • Tung Tran, Ramakanth Kavuluru
We introduce a novel neural architecture utilizing the table structure, based on repeated applications of 2D convolutions for pooling local dependency and metric-based features, that improves on the state-of-the-art without the need for global optimization.
Ranked #6 on Relation Extraction on CoNLL04
1 code implementation • EMNLP 2018 • Anthony Rios, Ramakanth Kavuluru
Furthermore, we develop few- and zero-shot methods for multi-label text classification when there is a known structure over the label space, and evaluate them on two publicly available medical text datasets: MIMIC II and MIMIC III.
no code implementations • WS 2018 • Anthony Rios, Tung Tran, Ramakanth Kavuluru
The second task (task B) asks participants to predict future psychological distress at ages 23, 33, 42, and 50 using the age 11 essays.
no code implementations • NAACL 2018 • Anthony Rios, Ramakanth Kavuluru
Coding EMRs with diagnosis and procedure codes is an indispensable task for billing, secondary data analyses, and monitoring health trends.
no code implementations • 5 Feb 2018 • Yifan Peng, Anthony Rios, Ramakanth Kavuluru, Zhiyong Lu
Text mining the relations between chemicals and proteins is an increasingly important task.
no code implementations • 26 Oct 2016 • A. K. M. Sabbir, Antonio Jimeno Yepes, Ramakanth Kavuluru
In this paper, we employ knowledge-based approaches that also exploit recent advances in neural word/concept embeddings to improve over the state-of-the-art in biomedical WSD using the MSH WSD dataset as the test set.