Northwestern University · BiologyStillbirth Research and Machine Learning Lab
Jeffery A Goldstein · Evanston, Illinois
Research Focus
Dr. Jeffery A Goldstein's lab focuses on using advanced machine learning techniques to understand the causes of stillbirth, a heartbreaking event affecting thousands of families each year. By analyzing placental histopathology, the lab aims to develop models that help identify placental issues leading to stillbirth, thereby improving diagnosis and treatment options. This research not only seeks to enhance understanding of stillbirth causes but also hopes to support families in their future pregnancies by providing personalized care based on identified risks.
machine learningstillbirthplacental histopathologydiagnosisneural networksartificial intelligencematernal healthclinical decision making
Research Aims
5AIM 01Develop machine learning models to identify placental causes of stillbirth.
AIM 02Analyze placental histopathology for key diagnoses related to stillbirth.
AIM 03Test the models on a large set of stillbirth cases to validate their effectiveness.
AIM 04Collaborate with pathologists and maternal-fetal medicine experts to classify causes of stillbirth.
AIM 05Improve decision-making in multidisciplinary conferences regarding stillbirth cases.
Skills the Lab Values
machine learningbioinformaticsstatistical analysisdata modelingclinical data abstractionplacental histology techniquescomputer programming (Python)data visualization
Output against the department
Publications386top 12% of dept.127th of 1,033
this lab
most publishedleast published
Citations11ktop 33% of dept.337th of 1,033
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.