Welcome to the live interview series, 'Transforming Healthcare with AI'.
AI in healthcare/biotech is a very rich space that has been garnering heightened attention with the deep learning and GPU-powered revolution over several years.
From the quality of life at home to surgical outcomes, from diagnosis to prognosis, from mental health to oncology, AI is everywhere.
The goal of this series is to tackle these topics one at a time to understand the nuances, the challenges, and the potential of each one of them. There are numerous unanswered questions as to how some of these models deal with data governance issues, biases, annotation quality, and regulatory frameworks.
This series will address some, if not all, of them in some measure. In this blog, we'll go over the basics of the live interview series and more, including:
Meet the host: Jagadish Venkatamaran
Jagadish Venkataraman has a Ph.D. in wireless communications and information theory from the University of Notre Dame. He spent the early parts of his career in the semiconductor industry, and later in the navigation industry. Hobby collaborations with a professor in UCSF in the biomedical engineering space triggered his passion for the Healthcare space.
He worked on machine vision applications for laparoscopic procedures at Stryker Endoscopy, and was later part of the early research team that laid the foundation for perception targets for the Verb/Verily surgical robot project to enhance surgeon experience both in real-time and offline.
At Calico Life Sciences, he led computer vision efforts in aging-related studies, both in yeast and in humans. Currently, he is Director of Machine Learning and Imaging AI at Tempus Labs, where he leads the radiology and cell imaging teams to discover prognostic imaging biomarkers in oncology as well as develop high throughput drug screening pipelines at scale.
What can you expect?
We’ll have engaging conversations between the host, Jagadish, and the guests. They’ll be experts in their field, and the conversation will get to the motivation behind their work, the approach, the challenges, model performances, and efforts to deploy them in real-world settings to touch patients’ lives.
These conversations will also reference and discuss popular publications in the area, so that you can do a deeper dive if you want.
The episode lineup
Starting with a guest introduction and then a story in their own words about what motivates their work, we’ll then have:
- A broad introduction of the topic under discussion
- The problem statement
- The state-of-the-art approach
- The novel approach to solving it
All in the guests’ own words.
We’ll also include data science/machine learning tips and tricks for the specific topics based on the guests’ experience for those at the beginning of their journey.
To finish the episodes, we’ll hear about the future directions for their work.
So, tune in and enjoy.