Mount Sinai Health System announced its new center for AI in Child Health on Monday. This explores directly into pediatric health care new ways to develop, test and implant AI to enable previous diagnostics, preventative approaches, and personalized treatment plans.
Why is it important?
To accelerate AI research and personalized treatment in child health, Mount Sinai said it will create an integrated data infrastructure, advance multimodal AI research and leverage computer-assisted imaging, multiomics research, rare disease identification and drug development to enhance the health economy and care delivery.
“Although AI has made an incredible progress in many areas of medicine, pediatric medicine is lagging behind due to stricter privacy considerations, more complex regulation pathways and limited data infrastructure,” said Benjamin Gricksberg, a digital health and clinical information expert.
Gricksberg, an associate professor of artificial intelligence and human health at Icahn School of Medicine in Mount Sinai, will lead the center. According to Dr. Brendan Kerr, Mount Sinai's CEO and renowned chairman of Kenneth L. Davis, he focuses on ensuring the health system provides more accurate diagnosis and personalized treatment for younger patients.
Founded under the Mindich Child Health and Development Institute, the center will also lead clinical trials at Mount Sinai Kravis Children's Hospital to enhance AI-driven diagnostics, predictive modeling and real-time monitoring.
“The Children's Health Centre highlights Mount Sinai's commitment to pioneering AI-driven technology that enables Mount Sinai to provide world-class care to children,” Kerr said in a statement.
“Our children are our future and, under Dr. Gricksberg's leadership, the AI Center in Child Health will promote child health outcomes for future generations,” added Dr. Girish Nadkarni, the Artificial Intelligence Bureau and Human Health Chair in Windereich Province, Mount Sinai.
Bigger trends
Health Systems uses AI imaging tools to improve patient access and treatment and predict disease.
Pediatric researchers at the Philadelphia Children's Hospital have developed deep learning models to increase understanding of disease progression, making AI available to others for tumor analysis.
The model can learn patterns and make predictions or classification faster than previous approaches, Chop researchers said.
“The approach can help you understand complex tissues at the cellular level and pave the way for a transformative breakthrough in healthcare,” said Kai Tan, the study's lead author and professor at the CHOP's Department of Pediatrics.
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“This new center is dedicated to addressing these challenges by developing, testing and implanting AI directly into children's healthcare. It enables previous diagnosis, preventative measures, computer-mediated imaging for complex conditions, rapid drug discovery and highly personalized treatment plans,” Glicksberg said in a statement.
“By leveraging the power of advanced data science and clinical expertise, we aim to guide a new era of healthcare for children, providing faster diagnosis, personalized treatments and transformative outcomes,” added Nadkarni.
Andrea Fox is a senior editor at Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.
