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Using AI in the Operating Room
FromDigital Health 101, by Dr. Stefano Bini and Digital Health Today
ratings:
Length:
32 minutes
Released:
Nov 25, 2021
Format:
Podcast episode
Description
In this episode, we are privileged to host Sanjeev Agrawal, President and CEO at LeanTaas. This is a healthcare software company that increases patient access to medical care. When Stefano first met Sanjeev at the first DocSF Conference, the company was just a start-up. Today, the company has grown into an established and well-funded company that is changing how we manage hospitals across the country.
Sanjeev recounts his healthcare entrepreneurial journal, which began when his team successfully solved a Stanford Cancer Institute problem. He discusses machine learning applications and gives excellent real-world examples of problems where machine learning can be applied. We also tackled the data they are looking for to solve problems and where machine learning is going in the future.
This conversation is fascinating, not just on how to solve complex healthcare problems utilizing accurate data, because there's more to it than that, so make sure to tune in!
About Sanjeev Agrawal
Sanjeev serves as the President and Chief Operating Officer for LeanTaaS. Sanjeev was Google's first Head of Product Marketing. Since then, he has led three successful startups - CEO at Aloqa (acquired by Motorola), VP Products & Marketing at TellMe Networks (acquired by Microsoft), and Founder & CEO at Collegefeed (acquired by After College).
Sanjeev graduated with a BS and MS in Electrical Engineering and Computer Science from MIT. He started his career at McKinsey & Company and Cisco Systems before joining Google. Sanjeev is a Forbes contributor and also writes on his blog at http://medium.com/@saagrawa. He is an avid squash player and has been named by Becker's Hospital Review as one of the top entrepreneurs innovating in Healthcare.
Key Takeaways:
LeanTaas cannot create volume, but it can help clinics and hospitals optimize patients physicians should be seeing.
The EHR has a historical record of all surgeries performed in the past by the block owner.
90% of a data science problem is the data. So science is important until you can extract meaning from it.
Most healthcare visits are not so simple.
Small data can make a world of difference.
Once you have clean data, then you can apply your algorithm.
Resources
Website: https://leantaas.com/
LinkedIn: https://www.linkedin.com/in/sanjeevagrawal2007/
Twitter: @saagrawa
Sanjeev recounts his healthcare entrepreneurial journal, which began when his team successfully solved a Stanford Cancer Institute problem. He discusses machine learning applications and gives excellent real-world examples of problems where machine learning can be applied. We also tackled the data they are looking for to solve problems and where machine learning is going in the future.
This conversation is fascinating, not just on how to solve complex healthcare problems utilizing accurate data, because there's more to it than that, so make sure to tune in!
About Sanjeev Agrawal
Sanjeev serves as the President and Chief Operating Officer for LeanTaaS. Sanjeev was Google's first Head of Product Marketing. Since then, he has led three successful startups - CEO at Aloqa (acquired by Motorola), VP Products & Marketing at TellMe Networks (acquired by Microsoft), and Founder & CEO at Collegefeed (acquired by After College).
Sanjeev graduated with a BS and MS in Electrical Engineering and Computer Science from MIT. He started his career at McKinsey & Company and Cisco Systems before joining Google. Sanjeev is a Forbes contributor and also writes on his blog at http://medium.com/@saagrawa. He is an avid squash player and has been named by Becker's Hospital Review as one of the top entrepreneurs innovating in Healthcare.
Key Takeaways:
LeanTaas cannot create volume, but it can help clinics and hospitals optimize patients physicians should be seeing.
The EHR has a historical record of all surgeries performed in the past by the block owner.
90% of a data science problem is the data. So science is important until you can extract meaning from it.
Most healthcare visits are not so simple.
Small data can make a world of difference.
Once you have clean data, then you can apply your algorithm.
Resources
Website: https://leantaas.com/
LinkedIn: https://www.linkedin.com/in/sanjeevagrawal2007/
Twitter: @saagrawa
Released:
Nov 25, 2021
Format:
Podcast episode
Titles in the series (14)
Trailer: Welcome to Digital Health 101: Explore and break down the building blocks of digital health, one technology at a time by Digital Health 101, by Dr. Stefano Bini and Digital Health Today