Here’s an interesting video on using Databricks to increase the efficiency of healthcare claim reimbursements.
Kurzgesagt – In a Nutshell explores what actually happens when it infects a human and what should we all do.
In December 2019 the Chinese authorities notified the world that a virus was spreading through their communities. In the following months it spread to other countries, with cases doubling within days. This virus is the “Severe acute respiratory syndrome-related coronavirus 2”, that causes the disease called COVID19, and that everyone simply calls Coronavirus.
Michael Hansen joins Scott Hanselman to explain what FHIR is and how to get started with FHIR on Azure. Fast Healthcare Interoperability Resources (or, FHIR) is a new standard for representing and exchanging healthcare data. Developed by the HL7 community to address problems with interoperability, pieces of healthcare data are represented as resources in FHIR (i.e, a patient is a resource, observation is a resource, etc.). Resources are healthcare data objects with properties (e.g., a patient has a name) and relationships. The FHIR specification also describes how to exchange these objects using a REST API. A FHIR server is a REST API that enables you to search, retrieve, modify, and delete healthcare data objects. Microsoft developed a first-party FHIR server, which is available as an open source project on GitHub and as a managed service, Azure API for FHIR.
In this video, the great and powerful Siraj Raval shows you how to build a healthcare startup with AI.
AI is set to disrupt every field and every industry. Healthcare, in particular, seems primed for disruption. Here’s an interesting project out of Stanford.
“One of the really exciting things about computer vision is that it’s this powerful measuring tool,” said Yeung, who will be joining the faculty of Stanford’s department of biomedical data science this summer. “It can watch what’s happening in the hospital setting continuously, 24/7, and it never gets tired.”
Current methods for documenting patient movement are burdensome and ripe for human error, so this team is devising a new way that relies on computer vision technology similar to that in self-driving cars. Sensors in a hospital room capture patient motions as silhouette-like moving images, and a trained algorithm identifies the activity — whether a patient is being moved into or out of bed, for example, or into or out of a chair.