Thrilled to be working with a fantastic team of investigators in what promises to be the largest federation in #BreastCancer #RiskAssessment, with #DigitalBreastTomosynthesis and #opensource privacy-preservation tools Columbia Radiology Columbia Vagelos College of Physicians & Surgeons Penn Radiology @PennMedEVDCSO

An incredible lineup of papers this year at the #GMML #NeurIPS23 Workshop! 📄 Check out accepted #orals and #posters here: openreview.net/group?id=NeurI… Thank you to all authors and reviewers for their outstanding work! We can't wait to see you there! 🙌 #Gaze #ML #DL #NeurIPS2023

Our own Sarthak Pati & @UjjwalBaid gave a hands-on tutorial to clinicians at #RSNA2023 in Chicago showcasing the Comprehensive Open Federated Ecosystem (COFE). #MachineLearning from diverse data while preserving #privacy, without coding! MLCommons, Federated Tumor Segmentation (FeTS) Initiative, IU School of Medicine, RSNA

🚀 Introducing the Stanford AIMI Dataset Index – a diverse inventory of AI-ready datasets for machine learning in healthcare! We hope this resource will help democratize access to health data for AI development. Explore & contribute here: bit.ly/3RmEGFL #AIMIDatasetIndex

Asian Americans represent many racial + ethnic communities, each with their own unique health challenges. Every voice is needed to create an accurate representation of the health of Asian Americans + improve health for everyone. Learn more: JoinAllofUs.org #JoinAllofUs

The zero-code Generally Nuanced #DeepLearning Framework (#GaNDLF) is featured as an Editors’ Choice Research Highlight of nature Communications Engineering Communications Engineering! Kudos to our #software architect Sarthak Pati for leading this industry-academia #OpenSource MLCommons effort.

Congrats to the MLCommons Medical working group for your nature recognition of the #GaNDLF framework, which combines AI with medical research enabling medical professionals to better diagnose and treat patients. #medicalai #ArtificialInteligence #healthtech

An analysis of genomic data from nearly 250K participants in the NIH’s AllofUsResearch identified more than 275 million previously unreported genetic variations, nearly 4 million of which have potential health consequences. Nature Medicine @VUMCgenetics spr.ly/6013nRz0R

At FIRST Robotics Competition in Houston #morethanrobots Sana Shah

Spyridon Bakas kicking off the Federated Learning tutorial at #ISBI2024. More talks and hands on session to follow! MLCommons Intel AI Federated Tumor Segmentation (FeTS) Initiative

Join us for BraTS focusing on Generalizability across tumors at IEEE International Symposium on Biomedical Imaging 2024 meeting @giemmecci Spyridon Bakas

Federated Learning in Healthcare tutorial at #ISBI2024 explored COFE, an ecosystem for clinical AI/ML development. MLCommons Medical WG presented #GaNDLF, #MedPerf, & #OpenFL for secure, multi-institution AI training & evaluation. mlcommons.org/2024/08/medper… #BiomedicalImaging

Really enjoyed my recent talk with Joe The Human Podcast in a casual conversation about work and life. youtube.com/watch?v=Fpef7L…

Prevention requires bold & forward-thinking investments. My OpEd on why letting funding lapse for AllofUsResearch would be a step backwards statnews.com/2024/09/03/all… STAT

IU School of Medicine researchers are leading a multi-site study to use a privacy-preserving artificial intelligence approach, called federated learning, to improve breast cancer risk prediction and reduce health inequities in cancer prevention care. bit.ly/4gd1SRr

Exciting news! We've launched a new study with @NIEHS to help researchers better understand how our environment can impact our risk for #Type2Diabetes and related complications. Read the announcement to learn more: allof-us.org/3UmmMnS

The latest episode of the #InTechnology podcast dives into the realm of #FederatedLearning and explores how this #AI technology is set to revolutionize data privacy and security. Watch the full episode now: intel.ly/4iyBjau

Emerging from machine learning (ML), federated learning (FL) allows builders to train on distributed datasets from different owners while maintaining full control of their personal data. Read on to learn how to enhance your #ML environment with OpenFL. intel.ly/4ggCzN4

Thank you Jennifer Schenker for another highly engaging interview. It was great to dive deep into #confidentialcomputing and share the ongoing work Intel is doing to keep our customers' data and organizations secure. Check out our conversation: tinyurl.com/mwx7xcwh