41 citations · 88 across the 4 of their papers we have counts for
4 papers
MedGemma Technical Report
Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78
Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks,…
TxGemma: Efficient and Agentic LLMs for Therapeutics
Eric Wang, Samuel Schmidgall, Paul F. Jaeger +6
Therapeutic development is a costly and high-risk endeavor that is often plagued by high failure rates. To address this, we introduce TxGemma, a suite of efficient, generalist larg…
Tx-LLM: A Large Language Model for Therapeutics
Juan Manuel Zambrano Chaves, Eric Wang, Tao Tu +7
Developing therapeutics is a lengthy and expensive process that requires the satisfaction of many different criteria, and AI models capable of expediting the process would be inval…
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…