1 code implementation • NAACL (BioNLP) 2021 • Preethi Raghavan, Jennifer J Liang, Diwakar Mahajan, Rachita Chandra, Peter Szolovits
We perform experiments to validate the quality of the dataset and set benchmarks for question to logical form learning that helps answer questions on this dataset.
no code implementations • NAACL (BioNLP) 2021 • Diwakar Mahajan, Ching-Huei Tsou, Jennifer J Liang
In our system, we first used a transformer-based encoder-decoder model to generate top N candidate impression summaries for a report, then trained another transformer-based model to predict a 14-observations-vector of the impression based on the findings and background of the report, and finally, utilized this vector to re-rank the candidate summaries.
no code implementations • BioNLP (ACL) 2022 • Jennifer J Liang, Eric Lehman, Ananya Iyengar, Diwakar Mahajan, Preethi Raghavan, Cindy Y. Chang, Peter Szolovits
Clinical risk scores enable clinicians to tabulate a set of patient data into simple scores to stratify patients into risk categories.
1 code implementation • 25 Oct 2024 • Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi, Diwakar Mahajan, Hongyang Li, Yuxin Yang, Elif Eyigoz, Aldo Guzman Saenz, Daniel E. Platt, Timothy H. Rumbell, Kenney Ng, Sanjoy Dey, Myson Burch, Bum Chul Kwon, Pablo Meyer, Feixiong Cheng, Jianying Hu, Joseph A. Morrone
We show that the multi-view models perform robustly and are able to balance the strengths and weaknesses of specific views.
1 code implementation • 18 Jun 2023 • Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan, Subhajit Chaudhury, Chulaka Gunasekara, Maxwell Crouse, Diwakar Mahajan, Ibrahim Abdelaziz, Achille Fokoue, Pavan Kapanipathi, Salim Roukos, Alexander Gray
In this work, we propose a new evaluation scheme to model human judgments in 7 NLP tasks, based on the fine-grained mismatches between a pair of texts.
1 code implementation • 16 Feb 2023 • Eric Lehman, Evan Hernandez, Diwakar Mahajan, Jonas Wulff, Micah J. Smith, Zachary Ziegler, Daniel Nadler, Peter Szolovits, Alistair Johnson, Emily Alsentzer
To investigate this question, we conduct an extensive empirical analysis of 12 language models, ranging from 220M to 175B parameters, measuring their performance on 3 different clinical tasks that test their ability to parse and reason over electronic health records.
no code implementations • 17 Aug 2022 • Giridhar Kaushik Ramachandran, Kevin Lybarger, Yaya Liu, Diwakar Mahajan, Jennifer J. Liang, Ching-Huei Tsou, Meliha Yetisgen, Özlem Uzuner
An accurate and detailed account of patient medications, including medication changes within the patient timeline, is essential for healthcare providers to provide appropriate patient care.
no code implementations • SEMEVAL 2021 • Nancy X. R. Wang, Diwakar Mahajan, Marina Danilevsk. Sara Rosenthal
In sub-task A, the goal was to determine if a statement is supported, refuted or unknown in relation to a table.
no code implementations • 17 Nov 2020 • Diwakar Mahajan, Jennifer J Liang, Ching-Huei Tsou
Understanding medication events in clinical narratives is essential to achieving a complete picture of a patient's medication history.
no code implementations • 2 Sep 2020 • Parthasarathy Suryanarayanan, Ching-Huei Tsou, Ananya Poddar, Diwakar Mahajan, Bharath Dandala, Piyush Madan, Anshul Agrawal, Charles Wachira, Osebe Mogaka Samuel, Osnat Bar-Shira, Clifton Kipchirchir, Sharon Okwako, William Ogallo, Fred Otieno, Timothy Nyota, Fiona Matu, Vesna Resende Barros, Daniel Shats, Oren Kagan, Sekou Remy, Oliver Bent, Pooja Guhan, Shilpa Mahatma, Aisha Walcott-Bryant, Divya Pathak, Michal Rosen-Zvi
We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6, 000 NPIs implemented worldwide since the start of the pandemic.
no code implementations • 21 May 2020 • Diwakar Mahajan, Jennifer J. Liang, Ching-Huei Tsou
Medication timelines have been shown to be effective in helping physicians visualize complex patient medication information.