2 citations · 2 across the 3 of their papers we have counts for
4 papers
Debias-CLR: A Contrastive Learning Based Debiasing Method for Algorithmic Fairness in Healthcare Applications
Ankita Agarwal, Tanvi Banerjee, William Romine +1
Artificial intelligence based predictive models trained on the clinical notes can be demographically biased. This could lead to adverse healthcare disparities in predicting outcome…
Mining Themes in Clinical Notes to Identify Phenotypes and to Predict Length of Stay in Patients admitted with Heart Failure
Ankita Agarwal, Tanvi Banerjee, William L. Romine +3
Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnosti…
Leveraging Natural Learning Processing to Uncover Themes in Clinical Notes of Patients Admitted for Heart Failure
Ankita Agarwal, Krishnaprasad Thirunarayan, William L. Romine +3
Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalizat…
Improving the Factual Accuracy of Abstractive Clinical Text Summarization using Multi-Objective Optimization
Amanuel Alambo, Tanvi Banerjee, Krishnaprasad Thirunarayan +1
While there has been recent progress in abstractive summarization as applied to different domains including news articles, scientific articles, and blog posts, the application of t…