100 citations · 763 across the 51 of their papers we have counts for
18 papers · 1 filter
Health AI Developer Foundations
Atilla P. Kiraly, Sebastien Baur, Kenneth Philbrick +23
Robust medical Machine Learning (ML) models have the potential to revolutionize healthcare by accelerating clinical research, improving workflows and outcomes, and producing novel…
General Geospatial Inference with a Population Dynamics Foundation Model
Mohit Agarwal, Mimi Sun, Chaitanya Kamath +31
Supporting the health and well-being of dynamic populations around the world requires governmental agencies, organizations and researchers to understand and reason over complex rel…
Selective Attention Improves Transformer
Yaniv Leviathan, Matan Kalman, Yossi Matias
Unneeded elements in the attention's context degrade performance. We introduce Selective Attention, a simple parameter-free change to the standard attention mechanism which reduces…
Earthquake magnitudes depend on seismic history, as revealed by a neural network analysis
Neri Berman, Oleg Zlydenko, Oren Gilon +2
Earthquake occurrence is notoriously difficult to predict. While some aspects of their spatiotemporal statistics can be relatively well captured by point-process models, very littl…
AI in Action: Accelerating Progress Towards the Sustainable Development Goals
Brigitte Hoyer Gosselink, Kate Brandt, Marian Croak +8
Advances in Artificial Intelligence (AI) are helping tackle a growing number of societal challenges, demonstrating technology's increasing capability to address complex issues, inc…
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach
Irina Jurenka, Markus Kunesch, Kevin R. McKee +71
A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about…
PathAlign: A vision-language model for whole slide images in histopathology
Faruk Ahmed, Andrew Sellergren, Lin Yang +14
Microscopic interpretation of histopathology images underlies many important diagnostic and treatment decisions. While advances in vision-language modeling raise new opportunities…
Towards a Personal Health Large Language Model
Justin Cosentino, Anastasiya Belyaeva, Xin Liu +31
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich,…
DoubleDipper: Improving Long-Context LLMs via Context Recycling
Arie Cattan, Alon Jacovi, Alex Fabrikant +8
Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal. In this work, we propose DoubleDipper, a novel…
Advancing Multimodal Medical Capabilities of Gemini
Lin Yang, Shawn Xu, Andrew Sellergren +44
Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Buil…
Multi-turn Reinforcement Learning from Preference Human Feedback
Lior Shani, Aviv Rosenberg, Asaf Cassel +10
Reinforcement Learning from Human Feedback (RLHF) has become the standard approach for aligning Large Language Models (LLMs) with human preferences, allowing LLMs to demonstrate re…
Capabilities of Gemini Models in Medicine
Khaled Saab, Tao Tu, Wei-Hung Weng +64
Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of…
Breaking the Language Barrier: Can Direct Inference Outperform Pre-Translation in Multilingual LLM Applications?
Yotam Intrator, Matan Halfon, Roman Goldenberg +5
Large language models hold significant promise in multilingual applications. However, inherent biases stemming from predominantly English-centric pre-training have led to the wides…
HeAR -- Health Acoustic Representations
Sebastien Baur, Zaid Nabulsi, Wei-Hung Weng +15
Health acoustic sounds such as coughs and breaths are known to contain useful health signals with significant potential for monitoring health and disease, yet are underexplored in…
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models
Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27
Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…
Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset
Abbi Ward, Jimmy Li, Julie Wang +17
Background: Health datasets from clinical sources do not reflect the breadth and diversity of disease in the real world, impacting research, medical education, and artificial intel…
Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings
Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong +23
Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little i…
Towards Conversational Diagnostic AI
Tao Tu, Anil Palepu, Mike Schaekermann +22
At the heart of medicine lies the physician-patient dialogue, where skillful history-taking paves the way for accurate diagnosis, effective management, and enduring trust. Artifici…