Networking Roundtables

How artificial intelligence can help oncologists see, and act on, “invisible” socioeconomic risk factors

Most oncologists agree that social determinants of health (SDOH) – such as financial, housing and food insecurity; social isolation; addiction; access to transportation and patient health literacy – can significantly impact cancer patient outcomes. In fact, a growing body of research has shown that SDOH are equally, if not more important in determining health outcomes than a patient’s genes.

A recent survey by Cardinal Health Specialty Solutions supports this assertion. 68% of the 160 oncologists surveyed said that more than half of their patients are negatively impacted by SDOH. Yet oncologists feel challenged to address the issues.  The survey showed that 81% don’t have enough time with patients to adequately understand or address their SDOH needs.

This roundtable will discuss how AI:

  • Drives better identification of high-risk patients
  • Optimizes oncology workflows
  • Enables better end of life planning

Moderator: John Frownfelter, MD, FACP, Chief Medical Officer, Jvion

How artificial intelligence can enable early detection of cancer and other chronic conditions

Statistics clearly show that early detection and intervention is currently the best method for combating cancer and achieving better patient outcomes. Proactive screening efforts for prevalent cancers have proven to be effective at detecting earlier-stage pre-symptomatic cancers; but how can developments in Ai be leveraged to detect these types of conditions outside of dedicated screening tests?

Zebra Medical Vision has been developing medical imaging algorithms that utilize CT scans that were not ordered specifically for cancer screening. These can call out potential opportunistic findings of underlying and unreported chronic conditions in patient populations at scale.

This roundtable will discuss how medical imaging AI:

  • Has traditionally been deployed for cancer screening
  • Can be utilized with existing imaging assets
  • Can learn to detect the precursors for conditions such as cancer

Moderator: Michael Callahan, US Director, Value Based Care, Zebra Medical Vision