With artificial intelligence technology, medical professionals can quickly and accurately sort through breast MRIs in patients with dense breast tissue to eliminate those without cancer.
Mammography...
Beckham Institute Biophotonics Imaging Laboratory researchers applied deep learning to polarization-sensitive optical coherence tomography (PS-OCT) to improve cancer diagnostic tools.
OCT systems are...
A study led by New York University (NYU) researchers created an artificial intelligence tool to improve the accuracy of breast cancer imaging. The computer program was trained to identify patterns...
Cleveland Clinic researchers collaborated with Owkin to develop and validate a deep learning model to predict survival and outcomes for hepatocellular carcinoma (HCC) patients after liver...
As providers strive to improve patient outcomes, the use of machine learning has become more integrated into the healthcare system. As this new form of technology continues to expand, it’s...
Artificial intelligence (AI) is making a dent in healthcare in the US and around the globe, helping leaders in Europe, South America, and Asia improve outcomes and cut costs, dissolving key pain points...
As providers search for ways to improve their methods of care, social determinants of health (SDOH) have become an increasingly popular area of research.
These social factors, which impact...
University of Los Angeles (UCLA) engineers developed a method to improve diagnostic tools that examine biopsied tissue samples using artificial intelligence. The AI system uses virtual re-staining of...
Data analytics serves as an essential tool when trying to close gaps in care. By studying data, providers can determine what steps need to be taken to improve patient outcomes.
Assistant Vice...
With the use of broad data collection, medical professionals can provide better care for their patients and eliminate health disparities. However, as health analytics advances to improve outcomes for...
Using predictive analytics is a critical step toward chronic disease prevention, allowing providers to recognize early signs of illness and intervene. While some may be at a higher risk of chronic...
To effectively document the severity of patient conditions and use risk stratification, the Community Health Network (CHN) in Indiana has streamlined hierarchical condition category (HCC) coding to...
Medical University of South Carolina (MUSC) researchers discovered a biomarker in blood samples that with predictive analytics can determine which patients will develop COVID-19 symptoms.
It remains...
By examining specific regions of the human genome, Baylor College of Medicine researchers developed a machine learning algorithm called SPLS-DA to look for epigenetic markers for schizophrenia.
The...
According to a recent study, physicians devote 62 percent of their time per patient reviewing electronic health records (EHRs), with the most time-consuming portion being clinical data review. To...
Researchers from the American Chemical Society have developed a blood test using predictive analytics to determine if individuals with COVID-19 will experience severe symptoms or not. According to the...
A team of researchers at Rensselaer Polytechnic Institute is creating new artificial technology techniques that protect algorithms from vulnerabilities such as contaminated data, malicious attacks, or...
With the COVID-19 pandemic highlighting gaps in healthcare and access to service, providers are searching for ways to improve the well-being of their members. By implementing predictive analytics,...
In a recent clinical study, scientists at Stanford University confirmed a new model of mental health treatment in which artificial intelligence therapy is implemented, significantly reducing symptoms...
Researchers from the Buck Institute and Stanford University have created an inflammatory clock for aging (iAge) that uses deep learning and predictive analytics to determine immunological health and...
