I completed an undergraduate degree in Biological Chemistry at the University of Toronto, followed by a medical degree at the Washington University School of Medicine in St. Louis, and residency in Anatomic and Clinical Pathology at Stanford Health Care (SHC). I am currently enrolled in the fellowship program in Molecular Genetic Pathology at SHC, and am slated to complete fellowship training in Surgical Pathology there as well. My interests include oncologic pathology, cardiothoracic pathology, molecular pathology, and applications of artificial intelligence and digital imaging in pathology.

Clinical Focus

  • Molecular Genetic Pathology
  • Oncologic Pathology
  • Cardiothoracic Pathology
  • Digital Pathology
  • Artificial Intelligence Applications in Pathology
  • Quality Assurance and Improvement
  • Fellow

Honors & Awards

  • Patient Safety Star Award, Stanford Health Care (March 2019)
  • Howard A. McCordock Prize in Pathology, Washington University School of Medicine (November 2014)
  • Antoinette Frances Dames Award in Cell Biology and Physiology, Washington University School of Medicine (November 2013)
  • Governor General's Silver Academic Medal, University of Toronto (June 2012)
  • John Black Aird Scholarship, University of Toronto (June 2012)
  • Chancellor's Gold Medal in Science, Trinity College, University of Toronto (June 2012)
  • Gordon Cressy Student Leadership Award, University of Toronto (March 2012)

Professional Education

  • MD, Washington University School of Medicine in St. Louis (2016)
  • BSc, Faculty of Arts and Science, University of Toronto, Biological Chemistry (2012)

Personal Interests

History, psychology, ethics


All Publications

  • Atypical Blastomycosis Masquerading as Lofgren Syndrome. American journal of respiratory and critical care medicine Shaller, B. D., Chen, S. B., Ho, D. Y., Yu, D. H. 2020

    View details for DOI 10.1164/rccm.201911-2158IM

    View details for PubMedID 32516540

  • NuSeT: A deep learning tool for reliably separating and analyzing crowded cells PLoS Computational Biology Yang, L., et al 2020
  • Impact of a deep learning assistant on the histopathologic classification of liver cancer. NPJ digital medicine Kiani, A., Uyumazturk, B., Rajpurkar, P., Wang, A., Gao, R., Jones, E., Yu, Y., Langlotz, C. P., Ball, R. L., Montine, T. J., Martin, B. A., Berry, G. J., Ozawa, M. G., Hazard, F. K., Brown, R. A., Chen, S. B., Wood, M., Allard, L. S., Ylagan, L., Ng, A. Y., Shen, J. 2020; 3: 23


    Artificial intelligence (AI) algorithms continue to rival human performance on a variety of clinical tasks, while their actual impact on human diagnosticians, when incorporated into clinical workflows, remains relatively unexplored. In this study, we developed a deep learning-based assistant to help pathologists differentiate between two subtypes of primary liver cancer, hepatocellular carcinoma and cholangiocarcinoma, on hematoxylin and eosin-stained whole-slide images (WSI), and evaluated its effect on the diagnostic performance of 11 pathologists with varying levels of expertise. Our model achieved accuracies of 0.885 on a validation set of 26 WSI, and 0.842 on an independent test set of 80 WSI. Although use of the assistant did not change the mean accuracy of the 11 pathologists (p?=?0.184, OR?=?1.281), it significantly improved the accuracy (p?=?0.045, OR?=?1.499) of a subset of nine pathologists who fell within well-defined experience levels (GI subspecialists, non-GI subspecialists, and trainees). In the assisted state, model accuracy significantly impacted the diagnostic decisions of all 11 pathologists. As expected, when the model's prediction was correct, assistance significantly improved accuracy (p?=?0.000, OR?=?4.289), whereas when the model's prediction was incorrect, assistance significantly decreased accuracy (p?=?0.000, OR?=?0.253), with both effects holding across all pathologist experience levels and case difficulty levels. Our results highlight the challenges of translating AI models into the clinical setting, and emphasize the importance of taking into account potential unintended negative consequences of model assistance when designing and testing medical AI-assistance tools.

    View details for DOI 10.1038/s41746-020-0232-8

    View details for PubMedID 32140566

    View details for PubMedCentralID PMC7044422

  • Quantification of Donor Liver Steatosis Using an Unsupervised Artificial Intelligence Platform Narayan, R., Abadilla, N., Yang, L., Hsu, C., Jensen, C., Chen, S. B., Higgins, J. P., Melcher, M. L. ELSEVIER SCIENCE INC. 2019: E151
  • Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA CANCER DISCOVERY Dudley, J. C., Schroers-Martin, J., Lazzareschi, D., Shi, W., Chen, S. B., Esfahani, M. S., Trivedi, D., Chabon, J. J., Chaudhuri, A. A., Stehr, H., Liu, C., Lim, H., Costa, H. A., Nabet, B. Y., Sin, M. Y., Liao, J. C., Alizadeh, A. A., Diehn, M. 2019; 9 (4): 500?509
  • Decidual granulomatous reaction in a placenta from a preeclamptic pregnancy: a case report and review of the literature VIRCHOWS ARCHIV Chen, S. B., Kudose, S., Krigman, H. R. 2018; 472 (4): 689?92


    We report a case of decidual perivascular non-necrotizing granulomas in a placenta from a pregnancy complicated by severe preeclampsia with no evidence of infection. The mother was a 20-year-old primigravida with severe preeclampsia diagnosed in the third trimester with subsequent delivery of a healthy baby boy at 37 weeks 5 days gestation. Pathologic examination of the placenta showed scattered non-necrotizing granulomas in decidua, often adjacent to remodeled decidual arteries without fibrinoid necrosis. These were well-formed, non-necrotizing granulomas with scant lymphoid cuffs. Polarization microscopy did not show foreign material. There were no histopathologic or clinical findings suggestive of maternal-fetal infection or systemic vasculitis at the time of delivery, and the mother had no other reported conditions associated with granulomatous inflammation. Our case demonstrates that granulomatous reaction may be seen in the placenta from a pregnancy complicated by severe preeclampsia, although work-up for infection may be indicated.

    View details for PubMedID 29541857

  • Detection of Large Chromosomal Abnormalities in Tumors through Analysis of Off-Target Next-Generation Sequencing (NGS) Read Data Chen, S. B., Stehr, H., Zehnder, J. L., Dudley, J. C. NATURE PUBLISHING GROUP. 2018: 804
  • Detection of Large Chromosomal Abnormalities in Tumors through Analysis of Off-Target Next-Generation Sequencing (NGS) Read Data Chen, S. B., Stehr, H., Zehnder, J. L., Dudley, J. C. NATURE PUBLISHING GROUP. 2018: 804
  • Detection and surveillance of bladder cancer using urine tumor DNA. Cancer discovery Dudley, J. C., Schroers-Martin, J., Lazzareschi, D. V., Shi, W. Y., Chen, S. B., Esfahani, M. S., Trivedi, D., Chabon, J. J., Chaudhuri, A. A., Stehr, H., Liu, C. L., Lim, H., Costa, H. A., Nabet, B. Y., Sin, M. L., Liao, J. C., Alizadeh, A. A., Diehn, M. 2018


    Current regimens for the detection and surveillance of bladder cancer (BLCA) are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage BLCA who either had urine collected prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per BLCA patient and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of BLCA. We detected utDNA pre-treatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96-100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, p=0.02) and cytology and cystoscopy combined (p is less than or equal to 0.006), detecting 100% of BLCA cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of BLCA.

    View details for PubMedID 30578357

  • Smooth-Muscle Myopathy in Systemic Lupus Erythematosus Presenting With Intestinal Pseudo-Obstruction. American journal of gastroenterology Yang, C., Chen, S., Gaut, J. P., Dehner, L. P. 2016; 111 (10): 1501-1502

    View details for DOI 10.1038/ajg.2016.328

    View details for PubMedID 27694873

  • Does the method of radiologic surveillance affect survival after resection of stage I non-small cell lung cancer? JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY Crabtree, T. D., Puri, V., Chen, S. B., Gierada, D. S., Bell, J. M., Broderick, S., Krupnick, A. S., Kreisel, D., Patterson, G. A., Meyers, B. F. 2015; 149 (1): 45-?


    Controversy persists regarding appropriate radiographic surveillance strategies after lung cancer resection. We compared the impact of surveillance computed tomography scan versus chest radiography in patients who underwent resection for stage I lung cancer.A retrospective analysis was performed of all patients undergoing resection for pathologic stage I lung cancer from January 2000 to April 2013. After resection, follow-up included routine history and physical examination in conjunction with chest radiography or computed tomography at the discretion of the treating physician. Identification of successive lung malignancy (ie, recurrence at any new site or new primary) and survival were recorded.There were 554 evaluable patients, with 232 receiving routine postoperative computed tomography and 322 receiving routine chest radiography. Postoperative 5-year survival was 67.8% in the computed tomography group versus 74.8% in the chest radiography group (P = .603). Successive lung malignancy was found in 27% (63/232) of patients receiving computed tomography versus 22% (72/322) receiving chest radiography (P = .19). The mean time from surgery to diagnosis of successive malignancy was 1.93 years for computed tomography versus 2.56 years for chest radiography (P = .046). For the computed tomography group, 41% (26/63) of successive malignancies were treated with curative intent versus 40% (29/72) in the chest radiography group (P = .639). Cox proportional hazard analysis indicated imaging modality (computed tomography vs chest radiography) was not associated with survival (P = .958).Surveillance computed tomography may result in earlier diagnosis of successive malignancy versus chest radiography in stage I lung cancer, although no difference in survival was demonstrated. A randomized trial would help determine the impact of postoperative surveillance strategies on survival.

    View details for DOI 10.1016/j.jtcvs.2014.07.095

    View details for Web of Science ID 000350550100018

    View details for PubMedID 25218540

  • Quantitative Analysis of the Effects of Photoswitchable Distance Constraints on the Structure of a Globular Protein BIOCHEMISTRY Beharry, A. A., Chen, T., Al-Abdul-Wahid, M. S., Samanta, S., Davidov, K., Sadovski, O., Ali, A. M., Chen, S. B., Prosser, R. S., Chan, H. S., Woolley, G. A. 2012; 51 (32): 6421-6431


    Photoswitchable distance constraints in the form of photoisomerizable chemical cross-links offer a general approach to the design of reversibly photocontrolled proteins. To apply these effectively, however, one must have guidelines for the choice of cross-linker structure and cross-linker attachment sites. Here we investigate the effects of varying cross-linker structure on the photocontrol of folding of the Fyn SH3 domain, a well-studied model protein. We develop a theoretical framework based on an explicit-chain model of protein folding, modified to include detailed model linkers, that allows prediction of the effect of a given linker on the free energy of folding of a protein. Using this framework, we were able to quantitatively explain the experimental result that a longer, but somewhat flexible, cross-linker is less destabilizing to the folded state than a shorter more rigid cross-linker. The models also suggest how misfolded states may be generated by cross-linking, providing a rationale for altered dynamics seen in nuclear magnetic resonance analyses of these proteins. The theoretical framework is readily portable to any protein of known folded state structure and thus can be used to guide the design of photoswitchable proteins generally.

    View details for DOI 10.1021/bi300685a

    View details for Web of Science ID 000307478700015

    View details for PubMedID 22803618

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