Machine learning tools can analyze certain types of retinal images to identify Alzheimer’s disease in symptomatic individuals, according to a study published in the British Journal of...
As big data analytics technologies continue to move from research labs to clinical settings, organizations are increasingly leveraging these tools to design more comprehensive cancer...
A machine learning tool was able to detect COVID-19 in x-ray images about ten times faster and one to six percent more accurately than specialized thoracic radiologists, according to a study published...
A team from Purdue University is leveraging artificial intelligence technology to collect and automatically measure the speech skills of people with Parkinson’s disease.
According to the...
A predictive analytics platform was able to accurately determine the probability of death or need for critical care within seven days for emergency department patients with COVID-19 symptoms, according...
Among the many possible applications of artificial intelligence and machine learning in healthcare, medical imaging is perhaps the most promising.
When used to decode the complicated nature of MRIs, CT scans, and other testing modalities,...
CMS has selected Geisinger as one of seven finalists in its Artificial Intelligence Health Outcomes Challenge.
In collaboration with Medial EarlySign, the health system used artificial intelligence...
A machine learning algorithm accurately determined how well skin cancer patients would respond to tumor-suppressing drugs in four out of five cases, according to research conducted by a team from NYU...
A real-time clinical decision support system issues alerts to specially trained nurses when patients are at risk of deteriorating, potentially leading to lower mortality rates, according to a study...
Machine learning models can predict the likelihood of critical illness or mortality in COVID-19 patients, which could help clinicians better care for and manage individuals infected with the virus,...
A simple machine learning approach predicted cirrhosis mortality risk as accurately as less interpretable algorithms, and also outperformed traditional risk methods, a study published in JAMA Network...
To learn more about how socioeconomic factors impact heart health, researchers are increasingly leveraging big data analytics technologies and examining social determinants data at the individual and...
Researchers in Carnegie Mellon University’s Robotics Institute were able to use machine learning technology to reduce food insecurity in Pennsylvania communities during the pandemic.
The team...
Combining formal instruction with practical problem-solving for fourth-year residents could accelerate the use of artificial intelligence in radiology, according to a report published in Radiology:...
Machine learning tools can predict the likelihood that a patient with a urinary tract infection (UTI) won’t respond to antibiotics, which could reduce antibiotic resistance in outpatient clinical...
A predictive analytics system was able to use location data to foresee flu outbreaks, outperforming other state-of-the-art forecasting tools with an eleven percent increase in accuracy.
The tool,...
A machine learning model was able to predict 90-day hospital readmissions with 85 percent accuracy, according to a study published in Health Services Research and Managerial Epidemiology....
A deep learning tool can offer more information about SARS-CoV-2 proteins to accelerate COVID-19 drug discovery, according to a study published in Chemical Science.
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In order to provide holistic, quality care for patients, clinicians have to address the non-clinical factors that influence overall wellness – individuals’ social determinants of...
A machine learning-based risk score can help providers identify COVID-19 patients who are most likely to experience negative outcomes, according to a study published in The Journal of Infectious...
