Daniel Rubin
Academic Appointments
- Assistant Professor, Radiology - Diagnostic Radiology
- Member, Bio-X
- Member, Stanford Cancer Institute
- Assistant Professor, Medicine - Biomedical Informatics Research
Key Documents
Contact Information
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Clinical Offices
Department of Radiology 300 Pasteur Dr MC 5105 Stanford, CA 94305 Tel Work (650) 723-6855
- Academic Offices
Personal Information Email Tel (650) 725-5693Alternate Contact Kelly Englese Administrative Associate Email Tel Work 650-723-9495Not for medical emergencies or patient use
Professional Overview
Clinical Focus
- Diagnostic Radiology
- Radiology
- Imaging informatics
- Biomedical informatics
- Quantitative Imaging
Honors and Awards
- caBIG Connecting Collaborators Award, National Cancer Institute (2010)
- Certificate of Merit, Radiological Society of North America (2009)
- Cum Laude Award, Radiological Society of North America (2008)
- Cum Laude Award, Radiological Society of North America (2006)
Professional Education
| Residency: | Stanford University Hospital (91) |
| Residency: | Stanford University School of Medicine CA (90) |
| Internship: | Stanford University School of Medicine CA (86) |
| Medical Education: | Stanford University School of Medicine CA (6/1/85) |
| Board Certification: | Diagnostic Radiology, American Board of Radiology (1990) |
Postdoctoral Advisees
Adrien Depeursinge, Daniel Golden, Camille Kurtz, Luis de Sisternes Garcia
Internet Links
Scientific Focus
Current Research Interests
My research interest is imaging informatics--ways computers can work with images to leverage their rich information content and to help physicians use images to guide personalized care. Just as biology has been revolutionized by online genetic data, now clinical medicine can be transformed by mining huge image repositories and electronically correlating image data with pathology and molecular data. Work in our lab thus lies at the intersection of biomedical informatics and imaging science, and we are working in several major areas. We are developing methods to extract information and meaning from images for data mining. We are also developing statistical natural language processing methods to extract and summarize information in radiology reports and published articles. We are building resources to integrate images with related clinical and molecular data to discover novel image biomarkers of disease. Finally, we are translating these methods into practice by creating decision support applications that relate radiology findings to diagnoses and that will improve diagnostic accuracy and clinical effectiveness.
Clinical Trials
Publications
- Automatic classification of mammography reports by BI-RADS breast tissue composition class. J Am Med Inform Assoc. 2012 Sep-Oct; (5): 913-6
- Informatics in radiology: improving clinical work flow through an AIM database: a sample web-based lesion tracking application. Radiographics. 2012 Sep-Oct; (5): 1543-52
- A comprehensive descriptor of shape: method and application to content-based retrieval of similar appearing lesions in medical images. J Digit Imaging. 2012; (1): 121-8
- Automatic Annotation of Radiological Observations in Liver CT Images. AMIA Annu Symp Proc. 2012: 257-63
- Modeling Perceptual Similarity Measures in CT Images of Focal Liver Lesions. J Digit Imaging. 2012
- Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results. Radiology. 2012; (2): 387-96
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