AI in Healthcare with Dale Markowitz

Google Cloud Platform Podcast - Podcast tekijän mukaan Google Cloud Platform

Kategoriat:

Gabi Ferrara joins Mark Mirchandani today for an in-depth interview with Dale Markowitz about machine learning in the healthcare and medical fields. Dale talks about the coolest ways ML is transforming the healthcare field with advances in imaging and more accurate diagnoses of cancers. Later, Dale talks about how the cloud is used in healthcare to make data collection and sharing more efficient. The Google For Healthcare API, for example, makes working with common medical data types such as FHIR easier and more consistent. It helps with things like anonymizing of data and works with BigQuery for data analyzation. When data is collected and stored in the right format, it can be used to track healing progress, make health predictions, and more. Dale Markowitz Dale Markowitz is an Applied AI Engineer and Developer Advocate at Google. Cool things of the week Google Game Developer Summit on Youtube videos Simplifying Google Drive’s folder structure and sharing models blog PostgreSQL 12 is in Beta on Google Cloud docs New 96-core machine types for MySQL, PostgreSQL and SQL Server Interview Google’s lung cancer detection AI outperforms 6 human radiologists article BigQuery site Cloud Healthcare API site Google FHIR docs Google Games Dev Summit Playlist videos Building Contact Center AI Solutions with Quantiphi - Stack Chat video Verily site DeepMind site AlphaFold: Improved protein structure prediction using potentials from deep learning research Computational predictions of protein structures associated with COVID-19 research How Machine Learning is Transforming Healthcare at Google and Beyond blog How to develop machine learning models for healthcare article Question of the week Where do I get started debugging performance for my MySQL database? Diagnose and Slow-Query Log Where can you find us next? Gabi will be working Office Hours. Mark will be making more videos like KubeFlow 101 Series and Stack Chat.

Visit the podcast's native language site