Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

The success of foundation models such as ChatGPT and AlphaFold has spurred significant
interest in building similar models for electronic medical records (EMRs) to improve patient …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

Irregular time series data is becoming increasingly prevalent with the growth of multi-sensor
systems as well as the continued use of unstructured manual data recording mechanisms …

In a world that has rapidly transformed through the advent of artificial intelligence (AI), our
systematic review, guided by the PRISMA protocol, investigates a decade of AI research …

Clinical notes contain information about patients that goes beyond structured data like lab
values and medications. However, clinical notes have been underused relative to structured …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Health care organizations are leveraging machine-learning techniques, such as artificial
neural networks (ANN), to improve delivery of care at a reduced cost. Applications of ANN to …

Acute critical illness is often preceded by deterioration of routinely measured clinical
parameters, eg, blood pressure and heart rate. Early clinical prediction is typically based on …

In recent years, there has been massive progress in artificial intelligence (AI) with the
development of deep neural networks, natural language processing, computer vision and …