ABOUT US
Learn more about us.
The Bitterman Lab is a research group within the AI in Medicine Program at Mass General Brigham and the Department of Radiation Oncology at Brigham and Women’s Hospital/Dana-Farber Cancer Institute, Harvard Medical School. We are a multidisciplinary team focused on developing, interrogating, and evaluating natural language processing approaches to improve our ability to learn from and care for patients. While broadly interested in the healthcare domain, we apply our expertise in clinical oncology to develop AI methods that improve cancer patients' experiences and outcomes.
Our current areas of active research include:
- Automated data mining from the electronic health records to accelerate cancer care and research.
- Language model evaluation and knowledge grounding for healthcare.
- Applying natural language processing advances to enhance health literacy and patient-provider communication.
- Translational AI: Clinical trials of AI and frameworks for ethical, patient-centered AI implementation.
Learn more about our Research, Publications, and Team.
Danielle Bitterman, MD
Principal Investigator
Assistant Professor, Harvard Medical School
Translating advances in natural language processing into safer and more equitable healthcare.
Recent Publications.
NEWS AND HIGHLIGHTS
Updates from the lab.
1 min read
Bitterman Lab research is featured in The New York Times!
Reporting on LLMs for patient portal messaging in the newspaper of record
BittermanLab
September 24, 2024
3 min read
Unveiling the fragility of language models to drug names
RABBITS: A new medical robustness investigation and LLM benchmark
BittermanLab
July 19, 2024
3 min read
Introducing Cross-Care
Our new benchmark to assess the healthcare implications of pre-training data on language model bias
BittermanLab
April 30, 2024
7 min read
Large language model assistance
Study out in Lancet Dig Health: How does using LLMs effect patient portal messaging?
BittermanLab
April 24, 2024
5 min read
LLMs for social determinants of health
LLM methods to detect SDoH from unstructured EHR text - published in npj Digital Medicine
BittermanLab
January 11, 2024
