The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-
4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with …

Deep learning has revolutionized many machine learning tasks in recent years, ranging
from image classification and video processing to speech recognition and natural language …

Missing data in time series is a pervasive problem that puts obstacles in the way of
advanced analysis. A popular solution is imputation, where the fundamental challenge is to …

Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …

Modeling continuous-time dynamics on irregular time series is critical to account for data
evolution and correlations that occur continuously. Traditional methods including recurrent …

Deep learning methods especially recurrent neural network based models have
demonstrated early success in disease risk prediction on longitudinal patient data. Existing …

Medication recommendation is an important healthcare application. It is commonly
formulated as a temporal prediction task. Hence, most existing works only utilize longitudinal …

Objectives Patient representation learning refers to learning a dense mathematical
representation of a patient that encodes meaningful information from Electronic Health …

Machine learning for healthcare researchers face challenges to progress and reproducibility
due to a lack of standardized processing frameworks for public datasets. We present MIMIC …

Effective modeling of electronic health records (EHR) is rapidly becoming an important topic
in both academia and industry. A recent study showed that using the graphical structure …