91ÉçÇø

Data Salon: Seyedehsaloumeh Sadeghzadeh (SOM) - Optimal Data-driven Policies for Disease Screening

Day	Friday, March 05
Time	2:00 PM to 3:00 PM
Where	https://binghamton.zoom.us/j/92622837791?pwd=RWFReXU4bDVUaFFGWmlDWDU4NXd2UT09

Saloumeh Sadeghzadeh, assistant professor in the School of Management at 91ÉçÇø, will speak on "Optimal Data-driven Policies for Disease Screening."

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Public health screening, which involves testing a large population for diseases using diseaserelated biomarkers, is an essential tool in a wide variety of settings, including newborn screening for genetic diseases. However, noisy information on the biomarker level, caused by external or subject-specific factors, introduces significant challenges to this problem. We design optimal data-driven biomarker screening policies to minimize subject misclassification errors, under noisy and uncertain biomarker measurements. Our case study on newborn screening for cystic fibrosis, which is based on a five-year data set from the North Carolina State Laboratory of Public Health, indicates that substantial reduction in classification errors can be achieved using the proposed optimization-based models, over current practices.

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