Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD codes to a medical note with average length of 3, 000+ tokens.
Ranked #1 on Medical Code Prediction on MIMIC-III
In this study, we first built Suicide Attempt and Ideation Events (ScAN) dataset, a subset of the publicly available MIMIC III dataset spanning over 12k+ EHR notes with 19k+ annotated SA and SI events information.
We show that membership inference attacks on CLMs lead to non-trivial privacy leakages of up to 7%.
Conversational Machine Comprehension (CMC), a research track in conversational AI, expects the machine to understand an open-domain natural language text and thereafter engage in a multi-turn conversation to answer questions related to the text.
We explore state-of-the-art neural models for question answering on electronic medical records and improve their ability to generalize better on previously unseen (paraphrased) questions at test time.
Pre-trained language models (LM) such as BERT, DistilBERT, and RoBERTa can be tuned for different domains (domain-tuning) by continuing the pre-training phase on a new target domain corpus.
We describe our approach towards building an efficient predictive model to detect emotions for a group of people in an image.
In this extended abstract, we lay the groundwork for a new family of methods under the P&C umbrella, known as Evolutionary Sampling (ES).