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Conquering Cough with Joe Brew from Hyfe

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Manage episode 374831913 series 3401994
Content provided by Heather D. Couture. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Heather D. Couture or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

These days, it seems that there are a lot of big problems in the world, especially in healthcare. Our guest today believes that there is massive value in tackling smaller problems, and, sometimes, the smaller problems are the most important to solve.

I welcome to the show today Joe Brew, Co-Founder and CEO of Hyfe, and he is here to talk about detecting and tracking coughing. We hear about what led to the founding of the company Hyfe and why they’ve narrowed their respiratory health innovations down to focus on cough. Joe talks about the role of machine learning, the process of gathering cough examples, and how they train their models. He touches on challenges they’ve faced, navigating model performance in varying environments, and the benefits of publishing their work. To hear more about why Joe believes now is the time to build this type of technology don’t miss out on this episode.

Key Points:

  • How the movement of pathogens through our bodies and communities eventually led to the founding of Hyfe.
  • What Hyfe does with respiratory health and why it’s important in overall healthcare.
  • Why they’ve narrowed their focus down to the cough.
  • The role machine learning plays in their cough-count technology.
  • He explains more about acoustic epidemiology.
  • The process of gathering cough examples and annotating them to train their models.
  • We explore the challenges faced working with and training models on audio data.
  • Navigating model performance in varying environments: working well in the real world.
  • Joe shares thoughts on the benefits of publishing their work.
  • Why now was the time to build this type of technology.
  • How Joe and his team are measuring the impact of their technology
  • Joe offers advice to other leaders of AI startups.
  • We talk about the potential impact of Hyfe in three to five years.

Quotes:

“I realized that there are so many global health problems that are addressable, at least partially by tech. I hesitate to say, solvable, but addressable.” — Joe Brew

“The really big problem that Hyfe is tackling is around respiratory health.” — Joe Brew

“It felt to us that cough is perhaps, the lowest-hanging fruit, the area where the additionality of tech is greatest, because it's so prevalent and because it's currently just the status quo is so poor.” — Joe Brew

“If you really want reliable medical grade annotations, you need reliable medical grade input. Garbage in, garbage out. That's why the only way to really do that is through partnerships with medical professionals.” — Joe Brew

“A method, that if I were to start another company or to do another project, I would absolutely repeat, is to go quickly to the market, start collecting data, real-world data really quickly, and build a feedback loop where you're constantly training, testing, validating on real-world data.” — Joe Brew

“Our aim is not just to get nice comments on the App Store or nice emails. It's to impact the lives of millions. Everybody who breathes has lungs and everybody with lungs coughs. We think cough tracking is for everybody.” — Joe Brew

“Don't be turned off by problems that appear simple. Sometimes the simplest problems are the ones that are the most important to solve.” — Joe Brew

Links:

Joe Brew on LinkedIn

Joe Brew on Twitter

Hyfe AI

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

Computer Vision Advisory Services – Monthly advisory services to help you strategically plan your CV/ML capabilities, reduce the trial-and-error of model development, and get to market faster.

  continue reading

84 episodes

Artwork
iconShare
 
Manage episode 374831913 series 3401994
Content provided by Heather D. Couture. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Heather D. Couture or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

These days, it seems that there are a lot of big problems in the world, especially in healthcare. Our guest today believes that there is massive value in tackling smaller problems, and, sometimes, the smaller problems are the most important to solve.

I welcome to the show today Joe Brew, Co-Founder and CEO of Hyfe, and he is here to talk about detecting and tracking coughing. We hear about what led to the founding of the company Hyfe and why they’ve narrowed their respiratory health innovations down to focus on cough. Joe talks about the role of machine learning, the process of gathering cough examples, and how they train their models. He touches on challenges they’ve faced, navigating model performance in varying environments, and the benefits of publishing their work. To hear more about why Joe believes now is the time to build this type of technology don’t miss out on this episode.

Key Points:

  • How the movement of pathogens through our bodies and communities eventually led to the founding of Hyfe.
  • What Hyfe does with respiratory health and why it’s important in overall healthcare.
  • Why they’ve narrowed their focus down to the cough.
  • The role machine learning plays in their cough-count technology.
  • He explains more about acoustic epidemiology.
  • The process of gathering cough examples and annotating them to train their models.
  • We explore the challenges faced working with and training models on audio data.
  • Navigating model performance in varying environments: working well in the real world.
  • Joe shares thoughts on the benefits of publishing their work.
  • Why now was the time to build this type of technology.
  • How Joe and his team are measuring the impact of their technology
  • Joe offers advice to other leaders of AI startups.
  • We talk about the potential impact of Hyfe in three to five years.

Quotes:

“I realized that there are so many global health problems that are addressable, at least partially by tech. I hesitate to say, solvable, but addressable.” — Joe Brew

“The really big problem that Hyfe is tackling is around respiratory health.” — Joe Brew

“It felt to us that cough is perhaps, the lowest-hanging fruit, the area where the additionality of tech is greatest, because it's so prevalent and because it's currently just the status quo is so poor.” — Joe Brew

“If you really want reliable medical grade annotations, you need reliable medical grade input. Garbage in, garbage out. That's why the only way to really do that is through partnerships with medical professionals.” — Joe Brew

“A method, that if I were to start another company or to do another project, I would absolutely repeat, is to go quickly to the market, start collecting data, real-world data really quickly, and build a feedback loop where you're constantly training, testing, validating on real-world data.” — Joe Brew

“Our aim is not just to get nice comments on the App Store or nice emails. It's to impact the lives of millions. Everybody who breathes has lungs and everybody with lungs coughs. We think cough tracking is for everybody.” — Joe Brew

“Don't be turned off by problems that appear simple. Sometimes the simplest problems are the ones that are the most important to solve.” — Joe Brew

Links:

Joe Brew on LinkedIn

Joe Brew on Twitter

Hyfe AI

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

Computer Vision Advisory Services – Monthly advisory services to help you strategically plan your CV/ML capabilities, reduce the trial-and-error of model development, and get to market faster.

  continue reading

84 episodes

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