Researchers are utilizing the power of machine learning to develop new models for identifying patients who may have post-acute sequelae of SARS-CoV-2 infection, or so-called “long COVID.” This interesting information came to us from Northeastern University in t heir article, “Researchers Use Machine Learning to Identify US Patients with Long COVID.”

Using emerging technologies like machine learning and artificial intelligence (AI) in healthcare is not new. This next phase is using electronic health records (EHRs) from a federal database that compiles medical information about COVID-19 patients to develop models that helped identify COVID long haulers across a range of features—from past COVID diagnosis, to the types of medications they’ve been prescribed.

This isn’t the first use of machine learning involved with COVID either. Other researchers how used clinical data to train machine learning models to predict the likelihood of hospitalization for individuals with COVID-19.

Understanding how the technology works is important. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.