Machine Learning at Abridge

We are a diverse team of experts in machine learning, including Carnegie Mellon University professors and their respective labs.

Want to research and validate with us? Join our team.

Ben Schloss, PhD

Abridge

Machine Learning

Dhruvesh Patel

Abridge

NLP Research Intern

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

Yiyuan Li

Abridge

Research Intern

Zack Lipton, PhD

Abridge

Advisor

Carnegie Mellon University

Assistant Professor

Let’s start a conversation.

July 24, 2020

Abridge

When we started Abridge a little over two years ago, we grounded ourselves in a simple statement: that healthcare is about stories. These stories could take many forms, starting with the conversations people have with their doctors, and extending into the updates they give their friends and family. Stories can also be found in the notes that are captured in official medical records, and in all the ways people offer support to others in their community...

A growing number of patients record their conversations with doctors. Here’s why.

July 24, 2020

Abridge

At 30, Steve Giallourakis, has had more experience with the healthcare system than most people have in their lifetimes. Giallourakis, a patient advocate who lives in the Cleveland area and is currently finishing his bachelor’s degree in advanced mathematics, was diagnosed with his first cancer when he was 15. He recently had surgery that successfully removed portions of one of his kidneys, part of the treatment for his fourth cancer. One of the most stressful and disorienting periods in his 15-year odyssey came last September.

Our approach to machine learning: Art + Science.

July 24, 2020

Sandeep Konam

We founded Abridge with the belief that conversations between patients and doctors provide some of the most important insights into how people can live healthier lives. While the ability to extract insights from those conversations has historically been challenging, the many recent advances in machine learning have generated an opportunity for us to bring more focus and understanding to people’s health.

Decode jargon faster with our new medical definitions feature.

July 30, 2020

Simon King

We’ve all been there. A doctor’s appointment with tons of jargon and complex instructions that leave our head spinning. If you’re like most of our users, that’s why you downloaded Abridge. But we often hear that gaining a better understanding of medical terms could be even faster. So today, we’ve made a big improvement with our “In this conversation” feature. Now, you’ll be able to see definitions for medical terms in the context of your conversation.

6 things we've learned about staying on top of your health — and how Abridge helps.

July 24, 2020

Abridge

At Abridge, our goal is to help people understand and follow through with every aspect of their health, so we continuously seek input on people’s needs to make sure we’re doing just that. Recently, we asked hundreds of people to tell us more about how they use Abridge and the impact it's had on their health. What really came through was that people have key challenges that Abridge solves for them — remembering the details, keeping people on the same page, and more. Here’s a summary of the 6 biggest things we learned.

No items found.

Machine learning helps us bring context & meaning to people’s health.

Our research powers the features people use to understand and follow through on their care.

What We’re Building

We are a diverse team of experts in machine learning, including Carnegie Mellon University professors and their respective labs.

Want to research and validate with us? Join our team.

Contributions to Research

Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations

Towards Understanding ASR Error Correction for Medical Conversations

ASR Error Correction and Domain Adaptation Using Machine Translation

Medication Regimen Extraction From Medical Conversations

Extracting Structured Data from Physician-Patient Conversations By Predicting Noteworthy Utterances

Encode-Decode

Let’s start a conversation.

A growing number of patients record their conversations with doctors. Here’s why.

Our approach to machine learning: Art + Science.

Decode jargon faster with our new medical definitions feature.

6 things we've learned about staying on top of your health — and how Abridge helps.