Sharing AI Rather than Data
The COVID-19 pandemic has dramatically expanded telehealth services and, with it, highlighted the need to share analytics across networks without moving data. Advanced telehealth systems are bringing video conferencing to the patient encounter, as well as a growing number of sensors capable of the continuous collection of physiological signals. The promise of applying Artificial Intelligence (AI) to all of this data for more personalized and wholistic diagnosis and treatment is threatened by communications challenges and eroding patient trust. Rural communities suffer from poor connectivity. The sudden increase in remote work and school has exacerbated network congestion. Ever more personal data is being transferred beyond the patient’s control or awareness. Data from millions of patients can be compromised in a single breach. In this presentation, we will explore how sharing analytics rather than data solves these problems and more. We will illustrate this with a number of different use cases for this transformational technology, including smart connected care. We will discuss why a standard for sharing analytics is vital to realize its benefits and how the emerging IEEE P2795 standard is addressing this.
Session ID: LT1616 Presentation Type: Live Session (Replay Available)
Date / Time: [Day 3] Wed. Sep. 16, 2020 @ 16:15 ET (US)
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