We need to chat about artificial intelligence With the arrival of large language models such as ChatGPT, AI is reshaping how we work and interact Long foretold and often dismissed, artificial intelligence (AI) is now reshaping how we work and interact as a society.1 For every claim that AI is overhyped and underperforming, only weeks or
“Note Bloat” impacts deep learning-based NLP models for clinical prediction tasks One unintended consequence of the Electronic Health Records (EHR) implementation is the overuse of content-importing technology, such as copy-and-paste, that creates “bloated” notes containing large amounts of textual redundancy. Despite the rising interest in applying machine learning models to learn from real-patient data, it
Early prediction of diagnostic-related groups and estimation of hospital cost by processing clinical notes As healthcare providers receive fixed amounts of reimbursement for given services under DRG (Diagnosis-Related Groups) payment, DRG codes are valuable for cost monitoring and resource allocation. However, coding is typically performed retrospectively post-discharge. We seek to predict DRGs and DRG-based case
Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support. Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in these records to improve clinical
