@KashPrime@emollick One of our next steps is to explore Med-Gemini capabilities with Google Cloud healthcare and life science customers and researchers; fill out our interest form if you want to stay up to date! https://t.co/tQJMNaqcdT
Excited to share latest ✨Med-Gemini✨ additions - our new research unlocks possibilities in medical data analysis with 3 new models built upon Gemini 1.5 that can handle 2D medical images, and for the first time genomic risk score & 3D radiology scans.
https://t.co/QKz0NZqpDH
.@ArterysInc became the first #healthcare company approved by the FDA for cloud-based clinical solutions that use #deeplearning. Learn how their product CardioAI enables clinicians to use a web browser to automatically measure cardiac parameters using #AI: https://t.co/LLo8zc4n5u
Here's the link to the latest AI Journal Club dealing with FDA approval of software. Very interesting as always!. Thanks to @judywawira for organizing! #RADAIJC
https://t.co/x5x3NkQkmW
Why are @ArterysInc executives @Fabienbeckers and @DanielIGolden so incredibly similar to pioneer Daniel Boone?
Find out at our @ACRRFS#MachineLearning journal club on FDA approval, TONIGHT at 5PM PST. Sign up and attend remotely: https://t.co/QjxMgjnNZ4
@ArterysInc Director of Machine Learning, @DanielIGolden is speaking on lung cancer detection and segmentation using #DeepLearning at the Deep Learning in Healthcare Summit in Boston on Friday #reworkHealth
We’re hiring for multiple positions on our ML team, including an ML Scientist and Data Engineer. Locations in San Francisco, Calgary and remote. A great chance to be part of the AI in Healthcare revolution!
https://t.co/vywIJAPE8O
Looking forward to speaking about our deep learning-powered lung nodule reference library at The Toronto Machine Learning Summit on March 28! https://t.co/lPjr3aXUC5
This man's creation of a fake Donald Trump tweet, which was mistaken for a real one, and his ensuing realization of what he has unleashed reads like a novel. https://t.co/Bj8aH8MugD
Arterys’ CardioAI generates clinician-preferred 2, 3, and 4 chamber views by locating cardiac landmarks in 3D data with Deep Learning. More info here: https://t.co/QERaL7supX, https://t.co/sVNBg9LnS8