Tag: Digital Health

Primer on Large Language Models and Healthcare Integration

This is a post that I have been planning to write for a while, but given the scope of change and constant expansion within this field it has proven difficult to stay up-to-date on the most current data models. That being said, large language models (LLM) are transforming all areas of medicine more quickly than … Continue reading Primer on Large Language Models and Healthcare Integration →

The Frontier of Atrial Fibrillation Detection

Atrial fibrillation (AF), a frequently encountered cardiac arrhythmia, presents notable diagnostic challenges to healthcare practitioners. Despite substantial advancements in cardiac care and technology, the early detection of AF continues to be an elusive task with important consequences. As I discussed in my last post, advances in artificial intelligence (AI) may be creating new avenues to assist … Continue reading The Frontier of Atrial Fibrillation Detection →

Atrial Fibrillation Screening: Can AI break the barrier?

Researchers at the Mayo Clinic published a study in 2019, showing that a convolutional neural network (CNN) enabled artificial intelligence (AI) algorithm could accurately predict the presence of paroxysmal atrial fibrillation (AF) from an electrocardiogram (ECG) taken in sinus rhythm (SR).  The study was groundbreaking in the sense that even expertly trained electrophysiologists are not … Continue reading Atrial Fibrillation Screening: Can AI break the barrier? →

SMART WARS: Atrial fibrillation vs consumer technology

The global prevalence of atrial fibrillation (AF) is over 60 million and increases steadily with age.  This estimate is widely expected to increase and almost double by 2050, reaching over 100 million.  AF is a major risk factor for stroke, accounting for up to 15-20% of all cases, and is a substantial economic burden on … Continue reading SMART WARS: Atrial fibrillation vs consumer technology →