2 citations · 2 across the 1 of their papers we have counts for
4 papers
Towards Multidisciplinary Summarization of Hospital Stays: Efficient Sentence-Level Clinical Provenance Categorization
Baris Karacan, Vaibhav Bhargava, Barbara Di Eugenio +21
Effective "all-team" summarization in high-complexity settings like the Neonatal Intensive Care Unit (NICU) requires aggregating insights from diverse disciplines (physicians, nurs…
Context-Aware Counterfactual Data Augmentation for Gender Bias Mitigation in Language Models
Shweta Parihar, Liu Guangliang, Natalie Parde +1
A challenge in mitigating social bias in fine-tuned language models (LMs) is the potential reduction in language modeling capability, which can harm downstream performance. Counter…
What Do LLMs Know About Alzheimer's Disease? Multi-loss Fine-Tuning and Probing for AD Detection
Lei Jiang, Yue Zhou, Natalie Parde
Reliable early detection of Alzheimer's disease (AD) is challenging, particularly due to the limited availability of labeled data. While large language models (LLMs) have shown str…
Using LLMs to Aid Annotation and Collection of Clinically-Enriched Data in Bipolar Disorder and Schizophrenia
Ankit Aich, Avery Quynh, Pamela Osseyi +5
NLP in mental health has been primarily social media focused. Real world practitioners also have high case loads and often domain specific variables, of which modern LLMs lack cont…