Discover the most effective run-time strategies on the OpenAI o1-preview model, improving accuracy in medical language tasks.
Microsoft’s Health and Life Sciences team has an exciting opportunity for an Applied Research Scientist to expand our Dragon Ambient eXperience (DAX) product to international markets. DAX listens to doctor/patient conversations and writes highly accurate…
Our organization, Microsoft Health Futures, is an interdisciplinary group of researchers, data scientists, computational biologists, bioinformaticians, engineers, physicians, and user experience researchers who are working to accelerate biomedical discovery. We apply the design thinking process…
RAD-DINO is a vision transformer model trained to encode chest X-rays using the self-supervised learning method DINOv2. RAD-DINO is described in detail in RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision (F. Pérez-García, H. Sharma, S.…
MAIRA-2 is a multimodal transformer designed for the generation of grounded or non-grounded radiology reports from chest X-rays. It is described in more detail in MAIRA-2: Grounded Radiology Report Generation (S. Bannur, K. Bouzid et al.,…
RadFact is a framework for the evaluation of model-generated radiology reports given a ground-truth report, with or without grounding. Leveraging the logical inference capabilities of large language models, RadFact is not a single number but a suite of…
Bioinformatics, biomedical natural language processing (NLP), and generative AI can play key roles in this transformation by discerning knowledge from data and separating signal from noise. We are looking for a Research Intern with experience…
