Radiology Tools For Precision Medicine With Ángel Alberich-Bayarri From Quibim Impact AI podcast

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://staging.podcastplayer.com/legal.

Impact AI »
Radiology Tools for Precision Medicine with Ángel Alberich-Bayarri from Quibim

1d ago 32:58

MP3•Episode home

How can we harness medical imaging and artificial intelligence to shift healthcare from reactive to predictive? In this episode, I sit down with Ángel Alberich-Bayarri to discuss how artificial intelligence is revolutionizing radiology and precision medicine. Ángel is the CEO of Quibim, a company recognized globally for its AI-powered tools that turn radiological scans into predictive biomarkers, enabling more precise diagnoses and personalized treatments.

In our conversation, we hear how his early work in radiology and engineering led to the founding of Quibim and how the company’s AI-based technology transforms medical images into predictive biomarkers. We unpack the challenges of data heterogeneity, how Quibim tackles image harmonization using self-supervised learning, and why accounting for regulations is critical when building healthcare AI products. Ángel also shares his perspective on the value of model explainability, the concept of digital twins, and the future of preventative imaging. Join us to discover how AI is disrupting clinical decision-making and preventive healthcare with Ángel Alberich-Bayarri.

Key Points:

Hear about Ángel’s background and how his career led to founding Quibim.
Find out how Quibim turns radiology images into predictive clinical insights.
Different use cases of Quibim’s technology and why biopsy data is important.
He explains why Quibim avoids relying solely on radiologist annotations.
Challenges of using medical imaging: data fragmentation and scanner variability.
Explore Quibim’s self-supervised image learning harmonization techniques.
How Quibim increases the explainability of the model while maintaining accuracy.
Why understanding clinical workflows and radiologist adoption behavior is critical.
Uncover how regulations influence the development of Quibim’s technology.
Ángel’s advice for entrepreneurs and leaders of AI-powered startups.
Quibim’s plans for predictive modeling, digital twins, and AI for preventative medicine.

Quotes:

“We would like AI to be able to mine all this hidden information we have right now in the images. Our vision is long-term, being able to understand what is happening until this point within the human body.” — Ángel Alberich-Bayarri

“What [Quibim is] investing in is the next frontier that not only detects and diagnoses disease, but also predicts or prognoses what is going to happen.” — Ángel Alberich-Bayarri

“Human behavior has a lot of nuances that need to be appreciated when AI is adopted.” — Ángel Alberich-Bayarri

“The bolder the claims you make, it’s the higher level of evidence you need to achieve.” — Ángel Alberich-Bayarri

“Taking care of health before we have symptoms, it’s just going to be a growing business, and therefore, a lot of AI tools will be needed to understand our inner us.” — Ángel Alberich-Bayarri

Links:

Ángel Alberich-Bayarri on LinkedIn

Ángel Alberich-Bayarri on X

Quibim

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.

125 episodes

#Tech #Business #Heather D. Couture #Machine Learning #Computer Vision #Deep Learning #Impact #Sustainability #Healthcare #Medical #Startup