Publications by authors named "Asal Bastani"
Article Synopsis
- The study aimed to evaluate the effectiveness of Natural Language Processing (NLP) using large language models (LLMs) like GPT-4 for identifying cirrhosis cohorts compared to traditional diagnosis code classification and manual chart review.
- A review of 3,788 discharge summaries revealed that LLM-based classification provided higher accuracy rates (up to 98.8%) for detecting cirrhosis and its complications, while code-based classification demonstrated lower positive predictive values (PPVs), especially for complex conditions.
- The findings indicate that LLMs could serve as a more efficient and precise alternative to code-based methods, potentially reducing the need for labor-intensive chart reviews in cirrhosis research.
Vaccine hesitancy is a major barrier to vaccination, hindering the success of vaccine efforts and thereby increasing public health risk to viral diseases, including COVID-19. Neurodivergent (ND) individuals, including individuals with an intellectual and/or developmental disability, have demonstrated a heightened risk of hospitalization and death due to COVID-19, highlighting the need for further research specifically on ND communities. We conducted a qualitative analysis using in-depth interviews with medical professionals, non-medical health professionals and communicators, and ND individuals or their caregivers.
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