University of Pennsylvania · Mathematics & StatisticsThe Diagnostic Discovery Lab
Jinbo Chen · Philadelphia, Pennsylvania
Research Focus
Dr. Jinbo Chen's lab focuses on improving how we identify patients who have diseases but haven't yet been diagnosed. Using electronic health records, or EHRs, the lab develops sophisticated statistical and machine learning methods to uncover under-diagnosed conditions like Primary Aldosteronism and Familial Hypercholesterolemia. The aim is to ensure better health care access and outcomes by understanding and addressing disparities in disease diagnosis.
under-diagnosiselectronic health recordsmachine learningstatistical methodshealth disparitieshealthcare accessEHR analysisdata-driven approachesdisease screeningpublic health
Research Aims
3AIM 01Develop statistical methods to identify under-diagnosed patients in electronic health records.
AIM 02Assess disparities in diagnosis rates among different patient subgroups.
AIM 03Create software tools to enhance identification of missed diagnoses in clinical settings.
Skills the Lab Values
statistical modelingmachine learning techniquesdata analysis with RPython programmingEHR data managementpredictive modelingrisk assessmentdata visualizationclinical research methodsethics in research
Output against the department
Publications222top 50% of dept.66th of 131
this lab
most publishedleast published
Citations4.8kbottom 34% of dept.86th of 131
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.