A computer program trained to see patterns among thousands of breast ultrasound images can aid physicians in accurately diagnosing breast cancer, a new study shows.
Tag: Artificial Intelligence
A combination of radiologists and AI reduced overdiagnosis and more accurately identified breast cancer in ultrasound exams.
Florian Knoll, incoming chair of imaging at University of Erlangen–Nuremberg, talks about his background, not being greedy, and why he does what he does.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which patients with COVID-19 would develop life-threatening complications within 4 days, a new study finds.
NYU Langone researchers won a deep learning challenge to detect lesions in digital breast tomosynthesis (DBT) images. We discuss the obstacles that DBT poses to deep learning and look at how our team navigated them.
The results could significantly improve the patient experience, expand access to MRIs, and potentially enable new use cases for MRI.
A look at how Linda Moy, MD, professor of radiology at NYU Langone Health is working with colleagues at NYU Center for Data Science on AI approaches to improve breast cancer screening.
An 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.
NIH-funded deep learning research at NYU Grossman School of Medicine promises to predict progression of knee osteoarthritis.
Imaging scientist Daniel Sodickson is collaborating with Facebook to make magnetic resonance imaging less burdensome for claustrophobic patients.