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Treść dostarczona przez Heather D. Couture. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Heather D. Couture lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
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Interpreting Infant Cries with Charles Onu from Ubenwa Health

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Manage episode 428975667 series 3401994
Treść dostarczona przez Heather D. Couture. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Heather D. Couture lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Infants cry when they're hungry, tired, uncomfortable, or upset. They also cry when they’re in pain or severely ill. But how can parents tell the difference? To help us address this critical question, I'm joined by Charles Onu, a health informatics researcher, software engineer, and CEO of Ubenwa. Ubenwa is a groundbreaking app that uses AI to interpret infants' needs and health by analyzing the biomarkers in their cries. Charles conceived of the idea while working in local communities in south-eastern Nigeria, where high rates of newborn mortality due to late detection of Perinatal Asphyxia inspired him to create a solution.

In this episode, Charles shares insights into Ubenwa's machine-learning models and how they establish an infant's cry as a vital sign. He discusses the process of collecting and annotating data through partnerships with children's hospitals, the challenges of working with audio data, the benefits of creating a foundation model for infant cries, and much more. He also offers human-focused advice for leaders of AI-powered startups and reflects on his vision for success and the impact he hopes to achieve with Ubenwa. Tune in to discover how understanding your infant’s cries can transform healthcare and well-being for newborns and their families!

Key Points:

  • Charles' converging interests in math and healthcare, which led him to create Ubenwa.
  • What Ubenwa does to establish an infant’s cry as a vital sign (and why it’s so important).
  • The essential end-to-end role that machine learning plays in this technology.
  • How Ubenwa collects and annotates data by partnering with children’s hospitals.
  • Challenges of working with audio data and training medical ML models on it.
  • Insight into the benefits of creating a foundation model for infant cries.
  • Variations in infant’s cries and how Ubenwa’s models generalize for these shifts.
  • Valuable research Ubenwa has made publicly available as a gift to the ML community.
  • Charles’ human-focused advice for other leaders of AI-powered startups.
  • What success means to Charles and the impact he hopes to make with Ubenwa.

Quotes:

“Ubenwa was born out of the idea that, if there's something that [human doctors] can listen to to come to a conclusion [about an infant’s health], then there has to be something machines can also learn from the infant's cry.” — Charles Onu

“The real leap we made with self-supervised learning is that you now do not need an external annotation to learn. The model can use the data to supervise itself.” — Charles Onu

“AI-powered or not, – the problem of a startup remains the same. It’s to meet a need that humans have. – At the end of the day, AI is not just there for AI only. It’s only going to be a successful and useful startup if you identify a need and [solve] that problem.” — Charles Onu

“Human babies have evolved to communicate their needs and their health through their cries. We [haven’t] had the tools to understand that. Babies have been trying to talk to us for a long time. It's time to listen.” — Charles Onu

Links:

Ubenwa Health

Nanni AI

Charles Onu on LinkedIn

Charles Onu on X

Charles Onu on GitHub

Ubenwa on GitHub

Ubenwa CryCeleb Database

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.

  continue reading

101 odcinków

Artwork
iconUdostępnij
 
Manage episode 428975667 series 3401994
Treść dostarczona przez Heather D. Couture. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Heather D. Couture lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Infants cry when they're hungry, tired, uncomfortable, or upset. They also cry when they’re in pain or severely ill. But how can parents tell the difference? To help us address this critical question, I'm joined by Charles Onu, a health informatics researcher, software engineer, and CEO of Ubenwa. Ubenwa is a groundbreaking app that uses AI to interpret infants' needs and health by analyzing the biomarkers in their cries. Charles conceived of the idea while working in local communities in south-eastern Nigeria, where high rates of newborn mortality due to late detection of Perinatal Asphyxia inspired him to create a solution.

In this episode, Charles shares insights into Ubenwa's machine-learning models and how they establish an infant's cry as a vital sign. He discusses the process of collecting and annotating data through partnerships with children's hospitals, the challenges of working with audio data, the benefits of creating a foundation model for infant cries, and much more. He also offers human-focused advice for leaders of AI-powered startups and reflects on his vision for success and the impact he hopes to achieve with Ubenwa. Tune in to discover how understanding your infant’s cries can transform healthcare and well-being for newborns and their families!

Key Points:

  • Charles' converging interests in math and healthcare, which led him to create Ubenwa.
  • What Ubenwa does to establish an infant’s cry as a vital sign (and why it’s so important).
  • The essential end-to-end role that machine learning plays in this technology.
  • How Ubenwa collects and annotates data by partnering with children’s hospitals.
  • Challenges of working with audio data and training medical ML models on it.
  • Insight into the benefits of creating a foundation model for infant cries.
  • Variations in infant’s cries and how Ubenwa’s models generalize for these shifts.
  • Valuable research Ubenwa has made publicly available as a gift to the ML community.
  • Charles’ human-focused advice for other leaders of AI-powered startups.
  • What success means to Charles and the impact he hopes to make with Ubenwa.

Quotes:

“Ubenwa was born out of the idea that, if there's something that [human doctors] can listen to to come to a conclusion [about an infant’s health], then there has to be something machines can also learn from the infant's cry.” — Charles Onu

“The real leap we made with self-supervised learning is that you now do not need an external annotation to learn. The model can use the data to supervise itself.” — Charles Onu

“AI-powered or not, – the problem of a startup remains the same. It’s to meet a need that humans have. – At the end of the day, AI is not just there for AI only. It’s only going to be a successful and useful startup if you identify a need and [solve] that problem.” — Charles Onu

“Human babies have evolved to communicate their needs and their health through their cries. We [haven’t] had the tools to understand that. Babies have been trying to talk to us for a long time. It's time to listen.” — Charles Onu

Links:

Ubenwa Health

Nanni AI

Charles Onu on LinkedIn

Charles Onu on X

Charles Onu on GitHub

Ubenwa on GitHub

Ubenwa CryCeleb Database

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.

  continue reading

101 odcinków

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