Lab News

April 2024

Check out newsletter "AHRQ Now" from the Agency for Healthcare Research and Quality (AHRQ) highlighting the continuous research of Tina Hernandez-Boussard, PhD. Her research has been continuously funded, in part from AHRQ.

Visit the AHRQ story for more

2024 AI Index Report Released

Seventh Edition of AI Index Report Now Available 

The AI Index Report offers unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI.

This year’s report measures and evaluates the rapid rate of AI advancement from research and development to technical performance and ethics, the economy and education, AI policy and governance, diversity, public opinion and more. The latest edition includes data from a broad set of academic, private, and non-profit organizations as well as more self-collected data and original analysis than any previous editions.

To see the full report click here.

Recent Publications

Attitudes on Coronary Artery Calcium

Our team utilized an AI pipeline of both supervised NLP models and unsupervised ML techniques to analyze social media discussions about Coronary Artery Calcium (CAC) in order to better describe contemporary attitudes around this risk marker of atherosclerotic cardiovascular disease. This study demonstrates the large potential of an AI-based approach to analyze large, publicly available social media data to generate insights into public perceptions about CAC, which may help guide strategies to improve shared decision-making around ASCVD management and public health interventions.

NPJ Digital Medicine

Sequence Modeling with Evo

In the ground-breaking preprint titled, "Sequence Modeling and Design from Molecular to Genome Scale with Evo,” we discuss how advances in machine learning combined with massive datasets of whole genomes (which encode DNA, RNA, and proteins) enable a biological foundation model that accelerates the mechanistic understanding and generative design of complex molecular interactions. Our team's contribution to this pioneering work encompasses the development of ethical considerations surrounding the application of Evo, a genomic foundation model boasting 7 Billion parameters. These ethical guidelines ensure that the advancements in multi-modal and multiscale learning facilitated by Evo are leveraged responsibly. Through our involvement, we highlight the importance of ethical practices in the cutting-edge domain of genomic modeling, ensuring that the potentials of Evo are realized with utmost consideration for ethical implications.

Cold Spring Harbor