Goal is more accurate tests, tools, and methodologies; $650K total prize purse
BOULDER, Colo., Sept. 7, 2023 /PRNewswire/ — DrivenData, the hub of data science competitions that advance solutions for social good, will support the National Institute on Aging (NIA)’s crowdsourced prize competition PREPARE: Pioneering Research for Early Prediction of Alzheimer’s and Related dementias EUREKA Challenge. HeroX, the social network for innovation and the world’s leading platform for crowdsourced solutions, will serve as an additional collaborator. The challenge aims to spur and reward the development of solutions for accurate, innovative, and representative early prediction of Alzheimer’s disease and related dementias.
Spanning across three phases, the challenge is designed to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes, particularly for communities disproportionately burdened by Alzheimer’s and related dementias.
“Alzheimer’s and related dementias affect millions of patients and families,” said Greg Lipstein, principal, DrivenData. “This challenge is a powerful opportunity to leverage advances in data and AI to equip care teams with greater capabilities for early prediction.”
“Being able to detect dementia diseases early can transform outcomes for impacted patients,” said Kal, CEO, HeroX. “We are thrilled this challenge is getting in front of innovators everywhere.”
The main clinical features of Alzheimer’s and related dementias are progressive impairments of cognitive function and changes in behavior. Early intervention will likely be important for successful disease modification, but detecting early signs of cognitive decline and Alzheimer’s and related dementias is challenging. Current clinical methods lack the sensitivity needed for early prediction. Alternative approaches (e.g., neuroimaging, fluid biomarkers, neuropsychological tasks, and digital and passive measures) have drawbacks, including cost, complexity, and accessibility. This is especially true for underrepresented populations in research.
“Early, accurate detection is important for enrollment in Alzheimer’s and related dementias trials and timely, accurate diagnosis is essential for treatment, care, and life planning,” said Luke Stoeckel, Ph.D., program director, at NIA, which is part of the National Institutes of Health. “Through challenges such as this one, NIA remains committed to increasing scientific collaboration, data sharing, and innovative research.”
The Challenge spans three phases:
The Prize total pool across the three challenge phases is $650,000, which will be awarded to participants who successfully complete the objectives and requirements of each phase.
To review the Eligibility to Win Prize(s) information and accept the challenge, please visit http://prepare.drivendata.org/. Information will also be available at www.challenge.gov/?challenge=prepare-challenge.
About DRIVENDATA
DrivenData is a social enterprise dedicated to bringing the data tools and methods that are transforming industry to the world’s biggest challenges. As part of that work, DrivenData’s competition platform channels the skills and passion of data scientists, researchers, and other quantitative experts to build solutions for social good. These online machine learning challenges are designed to engage a large expert community, connect them with real-world data problems, and highlight their best solutions.
ABOUT HEROX
HeroX is a platform and open marketplace for crowdsourcing innovation and human ingenuity, co-founded in 2013 by serial entrepreneur, Christian Cotichini and XPRIZE Founder and Futurist, Peter Diamandis. HeroX offers a turnkey, easy-to-use platform that supports anyone, anywhere, to solve everyday business and world challenges using the power of the crowd. Uniquely positioned as the Social Network for Innovation, HeroX is the only place you can build, grow and curate your very own crowd.
Explore the latest challenges at www.herox.com
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SOURCE DrivenData; HeroX
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