CSL professors among 2020 Jump ARCHES Grant recipients
Fourteen research projects, four co-led by CSL faculty, are sharing $1.9 million in funding through the Jump ARCHES research and development program. The Jump Applied Research for Community Health through Engineering and Simulation (Jump ARCHES), is a partnership between OSF HealthCare and the University of Illinois Grainger College of Engineering in Champaign-Urbana.
The ARCHES program supports research involving clinicians, engineers, and social scientists to develop technologies and devices that could revolutionize medical training and health care delivery. Faculty at the U of I College of Medicine at Peoria (UICOMP) also participate.
Since its inception in 2014, the Jump ARCHES initiative has directed more than $3.7 million for 39 projects.
The 14 new awards for 2020, range from $50,000 to $75,000. The four projects led by CSL faculty are:
Early detection of retinopathy in premature infants is important for early interventions to prevent blindness. With a shortage of specialists, it’s critically important to develop an AI diagnostic system that autonomously analyzes images of the retina to detect retinopathy. The team will also consider how to integrate the tool into portable, user-friendly equipment with the possibility future expanded uses for such a medical device.
Automated Aneurysm Segmentation and Measurement
Dr. Jeff Klopfenstein-OSF HealthCare and Thomas Huang-CSL
Cerebral aneurysms are among the most deadly types. This group will build a large-scale dataset to create an algorithm to identify and segment the bulging blood vessels based on size and blood flow. This will be used for future medical imaging instruction and to develop computer programs to help with treatment decisions.
Immediate feedback fosters the best learning and this project aims to improve Automated Short Answer Grading (ASAG) using Natural Language Processing (NLP) methods from previously collected and graded chart notes following simulations using standard participants (actor-based simulations). The tools developed will also reduce faculty grading demands and can be applied to trainings for other topics including use of opiates, telehealth use, patient counseling.
We propose applying advanced engineering and data science to develop a high-fidelity virtual simulator to provide thorough and validated microsurgical training and assessment. The team will develop an evidence-supported, automated, robust, real-time, comprehensive, quantitative (ARRCQ) assessment system by building data sets and creating algorithms for optimum learning including accuracy and cost.
A full list of the 14 awardees can be found here.