Abstract

Integrating AI Based Solutions into the Radiology Workflow - Stroke Use Case

In this presentation attendees can expect to gain a deeper understanding of the challenges and needs surrounding the integration of AI-based solutions into the clinical workflow, driving adoption and enabling maximal benefit. AI-based solutions have the potential to significantly improve healthcare processes, across the entire care-continuum. ....


Session No: SIL8144
Speaker: Tamar Schirman
Type:

AI in Healthcare

Date: Thursday - October 18, 2018 01:00 PM - 01:45 PM
Location: Hall M
Topics: Deep Learning and AI, AI in Healthcare
Industry: Healthcare & Life Sciences

In this presentation attendees can expect to gain a deeper understanding of the challenges and needs surrounding the integration of AI-based solutions into the clinical workflow, driving adoption and enabling maximal benefit. AI-based solutions have the potential to significantly improve healthcare processes, across the entire care-continuum. However, translating this potential into reality greatly depends on tight integration of these solutions into the clinical routine, else care-providers will not be able to adopt and benefit. In this talk, we will dive into the care pathway of acute stroke patients, as an example of a clinical workflow that stands to gain a great deal from automation and process efficiency. We will touch upon existing AI-based solutions that address specific challenges along the care trajectory and discuss how they could be integrated in the care-providers workflow, in order to yield maximal benefits.