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.
We partner with world leading research groups to further our technology and evidence of safety and effectiveness
Skin disease recognition using deep saliency features and multimodal learning of dermoscopy and clinical images
Zongyuan Ge, Sergey Demyanov, Rajib Chakravorty, Adrian Bowling, Rahil Garnavi
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Exploiting local and generic features for accurate skin lesions classification using clinical and dermoscopy imaging
Zongyuan Ge, Sergey Demyanov, Behzad Bozorgtabar, Mani Abedini, Rajib Chakravorty, Adrian Bowling, Rahil Garnavi
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Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective
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
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Tree-loss function for training neural networks on weakly-labelled datasets
Sergey Demyanov, Rajib Chakravorty, Zongyuan Ge, Seyedbehzad Bozorgtabar, Michelle Pablo, Adrian Bowling, Rahil Garnavi
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Improving Skin cancer Management with ARTificial Intelligence (SMARTI)
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
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