Type:
Preconference Forum
Session ID:
EXSUM-4
Title:
AI and the Proliferation of Intelligent and Predictive Technology
Description:
Al solution vendors are actively developing solutions-from diagnosis to care provision to patient monitoring-to help providers improve clinical outcomes. Others are working to improve resource utilization by both clinical and administrative staff. Philips is at the forefront of this development. While it is all the rage, most of Al is not generative. Most of it is developed within the framework of neural networks and machine learning models however, now is the inflection point to run experiments to see where solutions like generative Al fits: There are many places where Al could be applied clinically; A few examples are ECG analysis, rapid simple diagnostic analysis and workload optimization. Maybe potentially a chat bot to service technology installations with just-in-time instructions for clinical users. From the patient perspective, the value of generative Al turning clinical reports into lay speak is invaluable in helping to bridge the gap of medical literacy among other potential applications. While generative Al is being developed, Al solutions, like Philips own Caridologs, uses data from stroke patients, with 24 hours of consistent monitoring, to predict potential arrythmias occurring over the next week, thereby helping to reduce risk of a second stroke. Generative Al can continue to build on existing applications just like this one.
Level:
Intermediate
Learning Objective #1:
Learn where Al is being developed and deployed today
Learning Objective #2:
Learn how data, research, and deployment models support the continued development of more autonomous and capable Al solutions
Learning Objective #3:
Learn how healthcare systems and vendors are working together to create a better future for patients and clinicians