Here’s some news to still beating hearts: AI is helping bring some clarity to cardiology. Caristo Diagnostics has developed an AI-powered solution for detecting coronary inflammation in cardiac CT scans. In this episode of NVIDIA’s AI Podcast, Dr. Keith Channon, the Field Marshal Earl Alexander Professor at the University of Oxford, and the cofounder and chief medical officer at the startup, speaks with host Noah Kravtiz about the technology. Called Caristo, it analyzes radiometric features in CT scan data to identify inflammation in the fat tissue surrounding coronary arteries, a key indicator of heart disease. Tune in to learn more about how Caristo uses AI to improve treatment plans and risk predictions by providing physicians with a patient-specific readout of inflammation levels.
1:56: What is Caristo and how does it work?
7:11 The key signal of a heart attack
10:34 How did Channon come up with the idea of using AI to drive breakthroughs?
22:40 How much has the CT scan changed over the years?
26:01: What’s ahead for Caristo?
30:14: How to take care of your own heart health
Immunai Uses Deep Learning to Develop New Drugs – Ep. 176
What if we could map our immune system to create drugs that can help our bodies win the fight against cancer and other diseases? That’s the big idea behind immunotherapy. The problem: the immune system is incredibly complex. Enter Immunai, a biotechnology company using AI technology to map the human immune system and speed the development of new immunotherapies against cancer and autoimmune diseases.
Overjet on Bringing AI to Dentistry – Ep. 179
Dentists get a bad rap. Dentists also get more people out of more aggravating pain than just about anyone, which is why the more technology dentists have, the better. Overjet, a member of the NVIDIA Inception program for startups, is moving fast to bring AI to dentists’ offices.
Democratizing Drug Discovery With Deep Learning – Ep. 172
It may seem intuitive that AI and deep learning can speed up workflows — including novel drug discovery, a typically years-long and several-billion-dollar endeavor. But, professors Artem Cherkasov and Olexandr Isayev were surprised that no recent academic papers provided a comprehensive, global research review of how deep learning and GPU-accelerated computing impact drug discovery.
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