Azra Alizad, MD

Physician Scientist @MayoClinic. Cancer detection research, ultrasound innovation. #PedsID specialist. World traveler, proud mom. Tweets my own

[Gianrico Farrugia @GFarrugiaMD]

In a new study, Mayo researchers discovered a deep learning model trained on multi-parametric ultrasound data can remarkably improve the classification of metastatic and non-metastatic axillary lymph nodes in breast cancer patients:
https://t.co/GDr7BDX4Tr

[Gianrico Farrugia @GFarrugiaMD]

Researchers at Mayo are exploring the use of deep learning-based motion correction to improve the accurate classification of thyroid nodules as benign or malignant. Read the study: https://t.co/bUWz9cLZe6

[Azra Alizad, MD @AzraAlizad]

Excited about our technology providing high-resolution ultrasound images of tumor microvessls without using contrast agents, a potential noninvasive imaging tool for early cancer detection, prediction of metastasis and treatment monitoring.@MayoRadiology https://t.co/EQOcV4kmL3

[Mayo Clinic Radiology @MayoRadiology]

Dr. Azra Alizad, Dr. Mostafa Fatemi and their team developed and applied a new type of #Ultrasound, quantitative HDMI, with #RadAI to cancer detection and classification. Their research was profiled in @NIH Science Highlights. https://t.co/VKVs1P4bWV

[Azra Alizad, MD @AzraAlizad]

Very excited about this technology and proud of our research team!

[NIBIB @NIBIBgov]

A new automated cancer diagnostic technique from @MayoClinic could accurately tell benign thyroid nodules from malignant tumors. Find out how this AI-powered technique could potentially spare thousands of patients the trouble of surgery: https://t.co/1DSxMPanVU

@theNCI