Stanford University · BiologyThe Colorectal Innovation Lab
Jeanne Shen · Stanford, California
Research Focus
Dr. Jeanne Shen's lab focuses on improving treatment outcomes for colorectal cancer using advanced machine learning techniques. They are creating sophisticated models that analyze a combination of medical imaging, pathology slides, and clinical records to better predict patient risk and treatment effectiveness. The research aims to make these tools publicly available to help other researchers and clinicians enhance cancer care more broadly.
machine learningcolorectal cancerrisk stratificationdeep learningpathologyradiologyadjuvant therapybiomedical data sciencecancer biomarkersprecision medicine
Research Aims
5AIM 01Develop multimodal deep learning models for colorectal cancer risk stratification.
AIM 02Create a publicly available dataset of annotated colorectal cancer pathology and imaging data.
AIM 03Compare the effectiveness of multimodal models to single-modality models in patient risk assessment.
AIM 04Enhance precision medicine approaches for colorectal cancer by integrating diverse data types.
AIM 05Extend the developed models and dataset resources to other cancer types.
Skills the Lab Values
machine learningdeep learningpathology image analysisMRI interpretationCT scan analysisclinical data modelingdata annotationresearch collaborationdata visualizationPython programming
Output against the department
Publications157top 43% of dept.439th of 1,033
this lab
most publishedleast published
Citations5.6kbottom 41% of dept.609th 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.