Research

Everything we do at Kāhu is aligned to help the discovery and diagnosis of skin cancer. At every stage of our research and design phase, we’ve involved doctors, nurses and patients to ensure it’s safe and easy to use.

All our claims are substantiated below through reference to the associated publications.
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Featured Publications
We partner with world leading research groups to further our technology and evidence of safety and effectiveness
Zongyuan Ge, Sergey Demyanov, Rajib Chakravorty, Adrian Bowling, Rahil Garnavi
Skin disease recognition using deep saliency features and multimodal learning of dermoscopy and clinical images
Zongyuan Ge, Sergey Demyanov, Behzad Bozorgtabar, Mani Abedini, Rajib Chakravorty, Adrian Bowling, Rahil Garnavi
Exploiting local and generic features for accurate skin lesions classification using clinical and dermoscopy imaging
Tanja B. Jutzi, Eva I. Krieghoff-Henning, Tim Holland-Letz, Jochen Sven Utikal, Axel Hauschild, Dirk Schadendorf, Wiebke Sondermann, Stefan Fröhling, Achim Hekler, Max Schmitt, Roman C. Maron, and Titus J. Brinker1
Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective
Sergey Demyanov, Rajib Chakravorty, Zongyuan Ge, Seyedbehzad Bozorgtabar, Michelle Pablo, Adrian Bowling, Rahil Garnavi
Tree-loss function for training neural networks on weakly-labelled datasets
Claire Felmingham, Samantha MacNamara, William Cranwell, Narelle Williams, Miki Wada, Nikki R Adler, Zongyuan Ge, Alastair Sharfe, Adrian Bowling, Martin Haskett, Rory Wolfe, Victoria Mar
Improving Skin cancer Management with ARTificial Intelligence (SMARTI)
List of Claims & Substantiation
At Kāhu, we’re obsessed with the details. With getting it right. With backing up our claims. We believe that good clinical practice leads to good outcomes for patients.
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Whiteman D, Green A, Olsen C. The Growing Burden of Invasive Melanoma: Projections of Incidence Rates and Numbers of New Cases in Six Susceptible Populations through 2031. Journal of Investigative Dermatology. 2016;136(6):1161-1171 (https://www.cancerwa.asn.au/articles/news-2018/why-does-australia-have-so-much-skin-cancer-hint-i/)
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Balch CM, Soong SJ, Atkins MB, Buzaid AC, Cascinelli N, Coit DG, et al. An evidence-based staging system for cutaneous melanoma. CA Cancer J Clin 2004 May;54(3):131-49; quiz 182-4 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/15195788
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Petty AJ, Ackerson B, Garza R, Peterson M, Liu B, Green C, Pavlis M. Meta-analysis of number needed to treat for diagnosis of melanoma by clinical setting. J Am Acad Dermatol. 2020 May;82(5):1158-1165. doi: 10.1016/j.jaad.2019.12.063. Epub 2020 Jan 11. PMID: 31931085; PMCID: PMC7167347.
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Tschandl P, Rinner C, Apalla Z, Argenziano G, Codella N, Halpern A et al. Human–computer collaboration for skin cancer recognition. Nature Medicine. 2020;26(8):1229-1234.
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Elliott, T., Whiteman, D., Olsen, C. and Gordon, L., 2017. Estimated Healthcare Costs of Melanoma in Australia Over 3 Years Post-Diagnosis. Applied Health Economics and Health Policy, 15(6)
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Elliott, T., Whiteman, D., Olsen, C. and Gordon, L., 2017. Estimated Healthcare Costs of Melanoma in Australia Over 3 Years Post-Diagnosis. Applied Health Economics and Health Policy, 15(6).
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Skin cancer incidence and mortality - Skin Cancer Statistics and Issues. [online] Wiki.cancer.org.au. Available at: <https://wiki.cancer.org.au/skincancerstats/Skin_cancer_incidence_and_mortality>
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Guy, G., Machlin, S., Ekwueme, D. and Yabroff, K., 2015. Prevalence and Costs of Skin Cancer Treatment in the U.S., 2002−2006 and 2007−2011. American Journal of Preventive Medicine, 48(2)
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Skin Cancer as a Major Public Health Problem. [online] Available at: <https://www.ncbi.nlm.nih.gov/books/NBK247164/>
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https://www.racgp.org.au/afp/2012/july/skin-checks/
Singh DG, Boudville N, Corderoy R, Ralston S, Tait CP. Impact on the dermatology educational experience of medical students with the introduction of online teaching support modules to help address the reduction in clinical teaching. Australas J Dermatol 2011;52:264–9. Search PubMed
Rosendahl C, Williams G, Eley D, Wilson T, Canning G, Keir J, et al. The impact of subspecialization and dermatoscopy use on accuracy of melanoma diagnosis among primary care doctors in Australia. J Am Acad Dermatol 2012 Nov;67(5):846-52 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/22325462
Youl PH, Baade PD, Janda M, Del Mar CB, Whiteman DC, Aitken JF. Diagnosing skin cancer in primary care: how do mainstream general practitioners compare with primary care skin cancer clinic doctors? Med J Aust 2007 Aug 20;187(4):215-20 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/17708723
Wilkinson D, Bourne P, Dixon A, Kitchener S. Skin cancer medicine in primary care: towards an agenda for quality health outcomes. Med J Aust 2006 Jan 2;184(1):11-2 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/16398623.
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Shih S, Carter R, Heward S, Sinclair C. Skin cancer has a large impact on our public hospitals but prevention programs continue to demonstrate strong economic credentials. Australian and New Zealand Journal of Public Health. 2017;41(4):371-376.
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Hamidi R, Peng D, Cockburn M. Efficacy of skin self-examination for the early detection of melanoma. Int J Dermatol. 2010 Feb;49(2):126-34. doi: 10.1111/j.1365-4632.2009.04268.x. PMID: 20465635.
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Iannacone M, Green A. Towards skin cancer prevention and early detection: evolution of skin cancer awareness campaigns in Australia. Melanoma Management. 2014;1(1):75-84.
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Singh DG, Boudville N, Corderoy R, Ralston S, Tait CP. Impact on the dermatology educational experience of medical students with the introduction of online teaching support modules to help address the reduction in clinical teaching. Australas J Dermatol 2011;52:264–9. Search PubMed
Wilkinson D, Askew DA, Dixon A. Skin cancer clinics in Australia: workload profile and performance indicators from an analysis of billing data. Med J Aust 2006 Feb 20;184(4):162-4 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/16489899
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Singh DG, Boudville N, Corderoy R, Ralston S, Tait CP. Impact on the dermatology educational experience of medical students with the introduction of online teaching support modules to help address the reduction in clinical teaching. Australas J Dermatol 2011;52:264–9. Search PubMed
Rosendahl C, Williams G, Eley D, Wilson T, Canning G, Keir J, et al. The impact of subspecialization and dermatoscopy use on accuracy of melanoma diagnosis among primary care doctors in Australia. J Am Acad Dermatol 2012 Nov;67(5):846-52 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/22325462.
Youl PH, Baade PD, Janda M, Del Mar CB, Whiteman DC, Aitken JF. Diagnosing skin cancer in primary care: how do mainstream general practitioners compare with primary care skin cancer clinic doctors? Med J Aust 2007 Aug 20;187(4):215-20 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/17708723.
Wilkinson D, Bourne P, Dixon A, Kitchener S. Skin cancer medicine in primary care: towards an agenda for quality health outcomes. Med J Aust 2006 Jan 2;184(1):11-2 Abstract available at http://www.ncbi.nlm.nih.gov/pubmed/16398623.
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A.I. Here, There, Everywhere [Internet]. Nytimes.com. 2021 [cited 12 May 2021]. Available from: https://www.nytimes.com/2021/02/23/technology/ai-innovation-privacy-seniors-education.html
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Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94–98. https://www.rcpjournals.org/content/futurehosp/6/2/94
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Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94–98. https://www.rcpjournals.org/content/futurehosp/6/2/94
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Actual and potential harms caused by medical software [Internet]. Tga.gov.au. 2021 [cited 12 May 2021]. Available from: https://www.tga.gov.au/sites/default/files/actual-and-potential-harm-caused-medical-software.pdf
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Tschandl P, Rinner C, Apalla Z, Argenziano G, Codella N, Halpern A et al. Human–computer collaboration for skin cancer recognition. Nature Medicine. 2020;26(8):1229-1234.