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.

The Highlights

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.

Team

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

Publications

Contributions to Research

Weakly Supervised Medication Regimen Extraction from Medical Conversations

Dhruvesh Patel, Sandeep Konam and Sai Prabhakar

3rd Clinical Natural Language Processing Workshop, The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations

Benjamin J Schloss, Sandeep Konam

Proceedings of Machine Learning Research, Machine Learning for Healthcare (MLHC) 2020

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ASR Error Correction and Domain Adaptation Using Machine Translation

Anirudh Mani, Shruti Palaskar, Nimshi Venkat Meripo, Sandeep Konam, Florian Metze

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing

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