A recent study of 368 pregnant mothers, led by Bettina Cuneo, MD, director of perinatal cardiology and fetal cardiac telemedicine at Children's Hospital Colorado, found that fetal congenital heart disease (CHD) was correctly identified and successfully managed according to evidence-based risk stratification. In addition, parents achieved a dramatic cost benefit and patient/physician satisfaction was high.
Read more ...
AI Predicts which Pre-Malignant Breast Lesions will Progress to Advanced Cancer
New research at Case Western Reserve University could help better determine which patients diagnosed with the pre-malignant breast cancer commonly as stage 0 are likely to progress to invasive breast cancer and therefore might benefit from additional therapy over and above surgery alone.
Read more ...
Using Artificial Intelligence to Predict Risk of Thyroid Cancer on Ultrasound
Thyroid nodules are small lumps that form within the thyroid gland and are quite common in the general population, with a prevalence as high as 67%. The great majority of thyroid nodules are not cancerous and cause no symptoms. However, there are currently limited guidelines on what to do with a nodule when the risk of cancer is uncertain.
Read more ...
First Entirely Digital Clinical Trial Encourages Physical Activity
As little as a daily ping on your phone can boost physical activity, researchers from the Stanford University School of Medicine and their collaborators report in a new study. The finding comes by way of the first-ever entirely digital, randomized clinical trial, which sought to answer two overarching questions: Is it feasible to successfully run an entirely digital, randomized clinical trial?
Read more ...
AI could Offer Warnings about Serious Side Effects of Drug-Drug Interactions
The more medications a patient takes, the greater the likelihood that interactions between those drugs could trigger negative side effects, including long-term organ damage and even death. Now, researchers at Penn State have developed a machine learning system that may be able to warn doctors and patients about possible negative side effects that might occur when drugs are mixed.
Read more ...
Combination of AI & Radiologists more Accurately Identified Breast Cancer
An artificial intelligence (AI) tool - trained on roughly a million screening mammography images - identified breast cancer with approximately 90 percent accuracy when combined with analysis by radiologists, a new study finds. Led by researchers from NYU School of Medicine and the NYU Center for Data Science, the study examined the ability of a type of AI, a machine learning computer program, to add value to
Read more ...
Patients Say Ask before Using Medical Records for Research
With electronic medical records creating an ideal source of data to inform quality care and new discovery, a key question emerges: How much say should patients have in how their data is used? A new study led by Michigan Medicine researchers finds that even when patients understand the overall benefit to society, they still want to be able to give consent at least once before their de-identified data is used for research.
Read more ...