AI-HEAT: A Clinical Decision Support System for Pediatric Febrile Conditions

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AI-HEAT Research Objectives

The AI-HEAT project is a groundbreaking endeavor aimed at developing a deep learning-powered online platform to accurately distinguish between pediatric febrile conditions, including Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), Typhus and non-specific febrile illness. These conditions, while sharing several clinical presentations, require significantly different treatments. Early diagnosis and appropriate treatment are crucial for the best possible outcomes for patients with these diseases.

The AI-HEAT system utilizes state-of-the-art deep learning algorithms trained on datasets encompassing demographic, clinical and laboratory information to provide healthcare professionals with accurate and rapid diagnostic support. By leveraging data mining, AI-HEAT seeks to significantly reduce misdiagnosis rates and assist in timely intervention for KD, MIS-C and Typhus. This project represents a crucial step in improving pediatric healthcare, reducing the burden on healthcare systems, and ultimately saving lives. AI-HEAT strives to exemplify the potential of artificial intelligence in addressing complex clinical challenges and ensuring better outcomes for affected children.

Partners and Collaborators

We are an interdisciplinary team composed of members from University of Houston, Texas Children's Hospital and Rady Children's Hospital-San Diego.

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Join AI-HEAT's Mission

Be part of our mission to harness AI for differentiating between pediatric febrile conditions. Your contribution can help create a life-saving tool.

AI-HEAT

A Clinical Decision Support System for Pediatric Febrile Conditions

Reach out to us for collaborations, inquiries, or to learn more about our initiatives. We're based at the University of Houston and are eager to hear from you.

Contact

Computational Biomedicine Lab
c/o Ioannis A Kakadiaris
University of Houston
4349 MLK Blvd, Rm 322
Houston, TX 77204-6022

contact@aiheat.ai

Support

AI-HEAT is supported in part by R33HD105593. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s).