Daniel Rubin

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

Postdoctoral Advisees

Daniel Golden,  Daniel Golden,  Luis de Sisternes Garcia,  Luis de Sisternes Garcia

Internet Links

• Rubin web page

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

• Perfusion CT as a Predictor of Treatment Response in Patients with Rectal Cancer Recruiting

Publications

• A comprehensive descriptor of shape: method and application to content-based retrieval of similar appearing lesions in medical images. Xu J, Faruque J, Beaulieu CF, Rubin D, Napel S. J Digit Imaging. 2012; 25 (1): 121-8
• Current and future trends in imaging informatics for oncology. Levy MA, Rubin DL. Cancer J. 2011 Jul-Aug; 17 (4): 203-10
• A bayesian network for differentiating benign from malignant thyroid nodules using sonographic and demographic features. Liu YI, Kamaya A, Desser TS, Rubin DL. AJR Am J Roentgenol. 2011; 196 (5): W598-605
• A practical method for transforming free-text eligibility criteria into computable criteria. Tu SW, Peleg M, Carini S, Bobak M, Ross J, Rubin D, Sim I. J Biomed Inform. 2011; 44 (2): 239-50
• Evaluation of negation and uncertainty detection and its impact on precision and recall in search. Wu AS, Do BH, Kim J, Rubin DL. J Digit Imaging. 2011; 24 (2): 234-42