In the time since the COVID-19 outbreak has escalated to a full-blown global pandemic, buzzwords like artificial intelligence, population health management, and the social determinants of health have...
A team from Baylor College of Medicine’s Human Genome Sequencing Center is working to advance precision medicine by determining patients’ genetic risk factors for cardiovascular...
Cardiovascular factors typically evaluated in an annual physical, including blood pressure, cholesterol levels, diabetes, and smoking status, are just as accurate in predicting who will develop...
A simple predictive risk model helped forecast stroke risk in adult patients who have migraine with aura, according to research funded by the National Institute on Minority Health and Health...
Using structured and unstructured EHR data, machine learning algorithms could accurately identify patients at risk of developing Alzheimer’s disease and related dementias.
At least 50 percent of...
If the evolution of the healthcare industry were a jigsaw puzzle, then predictive analytics would be the last pieces put into place.
For years, experts have talked about the potential for artificial intelligence, machine learning,...
Using machine learning, researchers developed a more accurate model to predict hospital encounters for asthma patients, which could improve asthma outcomes and reduce care costs, according to a study...
Payers and providers need to understand the risk of their unique patient population to allocate financial and clinical resources. But an accurate risk score is contingent on holistic patient...
Risk scoring allows organizations to understand their population based on defined risk factors and anticipate the future risk of the group. A risk score is a metric used to predict aspects of a patient’s care (cost, risk of...
