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About Us

Oral cancer is the only major cancer whose outcomes continue to worsen.

Our goal is to turn this around. We are a multidisciplinary team of clinicians, scientists, engineers and medical device experts dedicated to creating a solution that can be used anywhere,

in any setting, by non-specialists.

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MISSION

To improve oral cancer outcomes through earlier and more accurate detection and monitoring 

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VISION

To ensure that, globally, everyone with oral cancer risk receives the earliest and best treatment.

Publications

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  1. Ilhan, B., Guneri, P., & Wilder-Smith, P. (2021). The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer. UC Irvine. Report #: ARTN 105254. http://dx.doi.org/10.1016/j.oraloncology.2021.105254
    Click here for Source

  2. Messadi, D., Wilder-Smith, P., & Wolinsky, L. (2009). Improving Oral Cancer Survival: The Role of Dental Providers. Journal of the California Dental Association, 37(11), 789-798. http://dx.doi.org/10.1080/19424396.2009.12223033
    Click here for Source 

  3. Le, A., Messadi, D., Epstein, J., & Wilder-Smith, P. (2011). Toward multimodality oral cancer diagnosis in the XXI century: Blending cutting edge imaging and genomic/proteomic definition of suspicious lesions. Bioinformation, 5(7), 304-306. http://dx.doi.org/10.6026/97320630005304
    Click here for source  

  4. Song, B.; Sunny, S.; Li, S.; Gurushanth, K.; Mendonca, P.; Mukhia, N., et al. (2021). Mobile-based oral cancer classification for point-of-care screening. Journal of Biomedical Optics, 26(6), 065003-065003. Report #: ARTN 065003. http://dx.doi.org/10.1117/1.jbo.26.6.065003
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  5. Birur, N.; Patrick, S.; Bajaj, S.; Raghavan, S.; Suresh, A.; Sunny, S., et al. (2018). A Novel Mobile Health Approach to Early Diagnosis of Oral Cancer. The Journal of Contemporary Dental Practice, 19(9), 1122-1128. http://dx.doi.org/10.5005/jp-journals-10024-2392
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  6. Nguyen, J.; Yang, S.; Melnikova, A.; Abouakl, M.; Lin, K.; Takesh, T., et al. (2023). Novel Approach to Improving Specialist Access in Underserved Populations with Suspicious Oral Lesions. Current Oncology, 30(1), 1046-1053. http://dx.doi.org/10.3390/curroncol30010080
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  7. Miranda-Hoover, A.; He, P.; Chau, T.; Cimba, M.; Francois, K.; Day, S., et al. (2024). Telehealth Utilization in Oral Medicine and Oral and Maxillofacial Surgery. Telemedicine Journal and e-Health, 30(3), 780-787. http://dx.doi.org/10.1089/tmj.2023.0099 Click here for Source 

  8. Nguyen, J., Takesh, T., Parsangi, N., Song, B., Liang, R., & Wilder-Smith, P. (2023). Compliance with Specialist Referral for Increased Cancer Risk in Low-Resource Settings: In-Person vs. Telehealth Options. Cancers, 15(10), 2775. Report #: ARTN 2775. http://dx.doi.org/10.3390/cancers15102775
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  9. Song, B.; Sunny, S.; Uthoff, R.; Patrick, S.; Suresh, A.; Kolur, T., et al. (2018). Automatic classification of dual-modalilty, smartphone-based oral dysplasia and malignancy images using deep learning. Biomedical Optics Express, 9(11), 5318-5329. http://dx.doi.org/10.1364/boe.9.005318
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  10. Uthoff, R.; Song, B.; Sunny, S.; Patrick, S.; Suresh, A.; Kolur, T., et al. (2019). Small form factor, flexible, dual-modality handheld probe for smartphone-based, point-of-care oral and oropharyngeal cancer screening. Journal of Biomedical Optics, 24(10), 106003-106003. Report #: ARTN 106003. http://dx.doi.org/10.1117/1.jbo.24.10.106003
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  11. Uthoff, R.; Song, B.; Sunny, S.; Patrick, S.; Suresh, A.; Kolur, T., et al. (2018). Point-of-care, smartphone-based, dual-modality, dual-view, oral cancer screening device with neural network classification for low-resource communities. PLOS ONE, 13(12), e0207493. Report #: ARTN e0207493. http://dx.doi.org/10.1371/journal.pone.0207493
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  12. Figueroa, K.; Song, B.; Sunny, S.; Li, S.; Gurushanth, K.; Mendonca, P., et al. (2022). Interpretable deep learning approach for oral cancer classification using guided attention inference network. Journal of Biomedical Optics, 27(1), 015001-015001. Report #: ARTN 015001. http://dx.doi.org/10.1117/1.jbo.27.1.015001
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  13. Song, B.; Li, S.; Sunny, S.; Gurushanth, K.; Mendonca, P.; Mukhia, N., et al. (2021). Classification of imbalanced oral cancer image data from high-risk population. Journal of Biomedical Optics, 26(10), 105001-105001. http://dx.doi.org/10.1117/1.jbo.26.10.105001
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  14. Song, B.; Sunny, S.; Li, S.; Gurushanth, K.; Mendonca, P.; Mukhia, N., et al. (2021). Bayesian deep learning for reliable oral cancer image classification. Biomedical Optics Express, 12(10), 6422-6430. http://dx.doi.org/10.1364/boe.432365 Retrieved from
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  15. DeCoro, M., & Wilder-Smith, P. (2010). Potential of optical coherence tomography for early diagnosis of oral malignancies. Expert Review of Anticancer Therapy, 10(3), 321-329. http://dx.doi.org/10.1586/era.09.191
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  16. Islip, D., Golabgir Anbarani, A., Wink, C., & Wilder-Smith, P. (2002). Comparing An Imaging-Based Versus Saliva-Based Approach To Determining Oral Cancer Risk. Journal of Dental Research, 81(1-Supplement), S6-S7.
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  17. Ahn, Y., Chung, J., Wilder-Smith, P., & Chen, Z. (2011). Multimodality approach to optical early detection and  mapping of oral neoplasia. Journal of Biomedical Optics, 16(7), 076007-076007-7. Report #: ARTN 076007. http://dx.doi.org/10.1117/1.3595850
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  18. Kim, C., Ingato, D., Wilder-Smith, P., Chen, Z., & Kwon, Y. (2018). Stimuli-disassembling gold nanoclusters for diagnosis of early-stage oral cancer by optical coherence tomography. Nano Convergence, 5(1), 3. Report #: ARTN 3. http://dx.doi.org/10.1186/s40580-018-0134-5
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  19. Wilder‐Smith, P., Jung, W., Brenner, M., Osann, K., Beydoun, H., Messadi, D., & Chen, Z. (2004). In vivo optical coherence tomography for the diagnosis of oral malignancy. Lasers in Surgery and Medicine, 35(4), 269-275. http://dx.doi.org/10.1002/lsm.20098
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  20. Chung, J., Jung, W., Hammer-Wilson, M., Wilder-Smith, P., & Chen, Z. (2007). Use of polar decomposition for the diagnosis of oral precancer. Applied Optics, 46(15), 3038-3045. http://dx.doi.org/10.1364/ao.46.003038
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  21. Wilder‐Smith, P., Lee, K., Guo, S., Zhang, J., Osann, K., Chen, Z., & Messadi, D. (2009). In vivo diagnosis of oral dysplasia and malignancy using optical coherence tomography: Preliminary studies in 50 patients. Lasers in Surgery and Medicine, 41(5), 353-357. http://dx.doi.org/10.1002/lsm.20773
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  22. Wilder-Smith, P., Krasieva, T., Jung, W., Zhang, J., Chen, Z., Osann, K., & Tromberg, B. (2005). Noninvasive imaging of oral premalignancy and malignancy. Journal of Biomedical Optics, 10(5), 051601-051601-8. Report #: ARTN 051601. http://dx.doi.org/10.1117/1.2098930
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  23. Mittal, R., Balu, M., Liu, G., Chen, Z., Tromberg, B., Wilder-Smith, P., & Potma, E. (2013). A Minimally Invasive Approach to The Challenge Of Oral Neoplasia. UC Irvine.
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  24. Matheny, E., Hanna, N., Jung, WG, Chen, Z., Wilder-Smith, P., Mina-Araghi, R., & Brenner, M. (2004). Optical coherence tomography of malignancy in hamster cheek pouches. Journal of Biomedical Optics, 9(5), 978-981. http://dx.doi.org/10.1117/1.1783897
    Click here for Source Retrieved from https://escholarship.org/uc/item/2mp4k0tm

  25. Jung, W., Zhang, J., Wang, L., Wilder-Smith, P., Chen, Z., McCormick, D., & Tien, N. (2005). Three-Dimensional Optical Coherence Tomography Employing a 2-Axis Microelectromechanical Scanning Mirror. IEEE Journal of Selected Topics in Quantum Electronics, 11(5), 806-810. http://dx.doi.org/10.1109/jstqe.2005.857683
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  26. Kim, C., Wilder-Smith, P., Ahn, Y., Liaw, L., Chen, Z., & Kwon, Y. (2009). Enhanced detection of early-stage oral cancer in vivo by optical coherence tomography using multimodal delivery of gold nanoparticles. Journal of Biomedical Optics, 14(3), 034008-034008-8. Report #: ARTN 034008. http://dx.doi.org/10.1117/1.3130323
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  27. Hanna, N.; Waite, W.; Taylor, K.; Jung, W.; Mukai, D.; Matheny, E., et al. (2006). Feasibility of Three-Dimensional Optical Coherence Tomography and Optical Doppler Tomography of Malignancy in Hamster Cheek Pouches. Photobiomodulation Photomedicine and Laser Surgery, 24(3), 402-409. http://dx.doi.org/10.1089/pho.2006.24.402
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  28. Sunny, S.; Agarwal, S.; James, B.; Heidari, E.; Muralidharan, A.; Yadav, V., et al. (2019). Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography. UC Irvine. http://dx.doi.org/10.1016/j.oraloncology.2019.03.006
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  29. Heidari, A.; Sunny, S.; James, B.; Lam, T.; Tran, A.; Yu, J., et al. (2019). Optical Coherence Tomography as an Oral Cancer Screening Adjunct in a Low Resource Settings. IEEE Journal of Selected Topics in Quantum Electronics, 25(1), 1-8. Report #: ARTN 7202008. http://dx.doi.org/10.1109/jstqe.2018.2869643
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  30. Song, B.; Li, S.; Sunny, S.; Gurushanth, K.; Mendonca, P.; Mukhia, N., et al. (2022). Exploring uncertainty measures in convolutional neural network for semantic segmentation of oral cancer images. Journal of Biomedical Optics, 27(11), 115001-115001. http://dx.doi.org/10.1117/1.jbo.27.11.115001
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  31. Song, B.; Zhang, C.; Sunny, S.; Kc, D.; Li, S.; Gurushanth, K., et al. (2023). Interpretable and Reliable Oral Cancer Classifier with Attention Mechanism and Expert Knowledge Embedding via Attention Map. Cancers, 15(5), 1421. Report #: ARTN 1421. http://dx.doi.org/10.3390/cancers15051421
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  32. James, B.; Sunny, S.; Heidari, A.; Ramanjinappa, R.; Lam, T.; Tran, A., et al. (2021). Validation of a Point-of-Care Optical Coherence Tomography Device with Machine Learning Algorithm for Detection of Oral Potentially Malignant and Malignant Lesions. Cancers, 13(14), 3583. Report #: ARTN 3583. http://dx.doi.org/10.3390/cancers13143583
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