Northwestern University · Biomedical EngineeringPulmonary Health and AI Group
Ulas Bagci · Evanston, Illinois
Research Focus
Ulas Bagci's lab focuses on harnessing advanced deep learning techniques to predict the risk of pulmonary fibrosis in patients who have recovered from COVID-19. This research aims to identify early indicators that could lead to better therapeutic interventions and a deeper understanding of lung health post-infection. The lab combines imaging data, such as CT scans, with electronic health records to create comprehensive predictive models that address a pressing public health need.
COVID-19pulmonary fibrosisdeep learningbiomarker discoverymachine learning
Research Aims
3AIM 01Identify imaging and electronic health record characteristics associated with post COVID-19 pulmonary fibrosis.
AIM 02Develop explainable deep learning algorithms to predict at-risk patients for pulmonary fibrosis.
AIM 03Establish a methodology for optimal biomarker discovery from multimodal data.
Skills the Lab Values
deep learningimage analysiselectronic health records (EHR)transformer modelsbiostatistics
Output against the department
Publications2bottom 1% of dept.589th of 595
this lab
most publishedleast published
Citations0bottom 1% of dept.590th of 595
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.