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Home » On Location at HIMSS 2023: How AI and ML Reduce Asthma Hospitalizations in Kids
AI and Copilots

On Location at HIMSS 2023: How AI and ML Reduce Asthma Hospitalizations in Kids

Toni WittBy Toni WittApril 24, 2023Updated:April 24, 20232 Mins Read
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Toni Witt was on location last week at the HIMSS23 Global Health Conference and Exhibition in Chicago. In this special report, Toni relates how a researcher showed a model that aims to reduce asthma hospitalizations in children through artificial intelligence (AI) and machine learning (ML).

This episode is sponsored by Acceleration Economy’s Generative AI Digital Summit. View the event, which features practitioner and platform insights on how solutions such as ChatGPT will impact the future of work, customer experience, data strategy, cybersecurity, and more, by registering for your free on-demand pass.

Highlights

00:43 — The researcher leading the session developed a model that aims to predict whether a pre-diagnosed patient with asthma would be hospitalized in the next 90 days based on a set of input factors. These factors include age, behaviors such as smoking, gender, ethnicity, and even the patient’s zip code — which are then ranked in terms of risk.

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01:09 — Based on the model’s outputs, the researchers would reach out to the high-risk children to notify them and encourage preventative measures. They also work with relevant local health organizations to take “real-world actions.”

01:26 — In terms of “real-world ROI,” Toni explains that “the project resulted in an estimated 166 asthma-related hospitalizations per year” that were “prevented because those in high risk were warned and then they were helped with preventative measures.”

01:44 — Not only does this translate to fewer lives lost but it also means there is less strain on the hospital system.

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01:59 — Toni considers this project to be a great example of “preventative care done through the lens of SDOH.” He explains how, this week, he learned about the term “Social Determinants of Health” which are non-medical factors that can impact someone’s health, such as socio-economic status.

02:14 — AI and ML are unlocking the use of SDOH data in the healthcare industry, which is a “hot topic” at HIMSS.


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Toni Witt

Co-founder, Sweet
Cloud Wars analyst

Areas of Expertise
  • AI/ML
  • Entrepreneurship
  • Partners Ecosystem
  • Website
  • LinkedIn

In addition to keeping up with the latest in AI and corporate innovation, Toni Witt co-founded Sweet, a startup redefining hospitality through zero-fee payments infrastructure. He also runs a nonprofit community of young entrepreneurs, influencers, and change-makers called GENESIS. Toni brings his analyst perspective to Cloud Wars on AI, machine learning, and other related innovative technologies.

  Contact Toni Witt ...

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