A team from NYU Langone Health analyzed EHR data and found that low levels of blood oxygen and markers of inflammation were strongly associated with poor outcomes among patients...
Certain risk scores already used to evaluate the severity of a trauma patient’s condition can also help providers determine which patients are highly likely to develop multiple infections,...
Researchers at the HudsonAlpha Institute for Biotechnology, the University of California, San Francisco (UCSF), and the University of Alabama at Birmingham (UAB) have uncovered a new genetic risk...
In the context of COVID-19, state-level decision-makers should conduct risk assessments to better understand how to move from strict social distancing measures to a staged reopening phase, according to...
In medicine, risk scoring is one of the best methods providers can use to anticipate and prepare for an adverse event. Using patient data and analytics tools, clinicians can determine the likelihood...
A genetic variant responsible for driving the development of inflammatory bowel disease (IBD) is associated with a genetic pathway that is involved in other immune disorders, indicating that this...
As the COVID-19 pandemic continues to disrupt the status quo, the healthcare industry is turning to real-world data to better understand, monitor, and prepare for whatever the virus may bring.
For...
Researchers from Stanford University’s department of surgery have developed a predictive model that provides best practice guidelines for operating room team members during the COVID-19 pandemic...
Using artificial intelligence, NYU researchers accurately predicted which patients newly diagnosed with COVID-19 would go on to develop severe respiratory disease, according to a study published in...
Mount Sinai researchers have developed new predictive analytics tools and identified environmental risk factors that could lead to a new understanding of what triggers Crohn’s disease.
In a...
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...
Machine learning tools could predict patients’ long-term risk of heart attacks and cardiac deaths better than standard methods used by cardiologists, according to a study published in...
Using a polygenic risk score based on data from genome-wide association studies (GWAS) improves psychosis risk prediction in patients meeting clinical high-risk criteria, according to a study published...
