Machine learning helps us bring context & meaning to people’s health.
a·bridge
/əˈbɹɪdʒ/
verb: shorten (a piece of writing) without losing the sense.
Our research powers the features people use to understand and follow through on their care.
What We’re Building
Proprietary, fully consented, and de-identified dataset, continually annotated with clinicians and researchers.
Machine learning-powered user experiences that bolster privacy and trust.
ML pipelines that are rigorously tested with patients and clinicians.
Publicly available and peer-reviewed research.
We are a diverse team of experts in machine learning, including Carnegie Mellon University professors and their respective labs.
Elisa Ferracane, PhD
Abridge - ML Research
Florian Metze, PhD
Abridge - Advisor, Co-Founder Carnegie Mellon University - Research Professor
Katerina Fragkiadaki, PhD
Carnegie Mellon University - Assistant Professor
Kundan Krishna
Carnegie Mellon University - PhD Student
Nimshi Venkat Meripo
Abridge - ML Ops
Sai Prabhakar
Abridge - ML Research
Sandeep Konam
Abridge - CTO, Co-Founder
Shruti Palaskar
Carnegie Mellon University - PhD Student
Zack Lipton, PhD
Abridge - Advisor Carnegie Mellon University - Assistant Professor
Contributions to Research
Weakly Supervised Medication Regimen Extraction from Medical Conversations
3rd Clinical Natural Language Processing Workshop, The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations
Proceedings of Machine Learning Research, Machine Learning for Healthcare (MLHC) 2020
ASR Error Correction and Domain Adaptation Using Machine Translation
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing
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