A Master’s Degree Student’s Story: Learning to analyze complex data and hitting the gym
First-year master’s degree student Zichun Xu chose the Yale School of Public Health to pursue his studies in biostatistics because of its world-class faculty and engaging academic environment. He particularly enjoys the school’s academic freedom to take classes in related disciplines across Yale. But student life is not all lectures and studying. In his downtime, Xu can often be found playing basketball at the Payne Whitney Gym or biting into a slice of New Haven’s world-famous pizza.
A Status Report on AI in Laboratory Medicine
Artificial intelligence (AI) models in healthcare have the potential to improve the precision and speed of personalized medicine for patients, in some cases helping to identify the best treatment or preventive care. Clinicians are already implementing these models in areas such as early detection of sepsis and analyzing radiology images for diagnosis of prostate cancer and other conditions. It’s a growing area of interest that laboratory medicine professionals should pay attention to, as data generated by laboratory testing is a major component incorporated into AI tools to generate clinical decisions.Source: AACC Clinical Laboratory News
AI-based model can use ECG images to diagnose multiple heart rhythm and conduction disorders
Researchers have developed an artificial intelligence-based model for clinical diagnosis that can use electrocardiogram (ECG) images, regardless of format or layout, to diagnose multiple heart rhythm and conduction disorders.Source: News-Medical.Net
Can an Image-based Electrocardiographic Algorithm Improve Access to Care in Remote Settings?
Researchers at the Yale Cardiovascular Data Science (CarDS) Lab have developed an artificial intelligence (AI)-based model for clinical diagnosis that can use electrocardiogram (ECG) images, regardless of format or layout, to diagnose multiple heart rhythm and conduction disorders.