Publications

Claims Substantiation

This website contains certain claims made by DermaSensor Pty. Ltd. (Australia) outlined below, that are substantiated through reference to the associated publications. For copies of these publications, please visit the associated websites referenced below.

CLAIMS #1 - “faster [and easier] route to reliable information”

SUBSTANTIATION: “Faster” when compared to other technologies that require extensive training, skin preparation and/or image interpretation. "ESS requires no skin preparation and is easy to administer, requiring minimal practitioner training. [It] generates a simple dichotomous output in a non-invasive way." (Rodriguez-Diaz et al (Photochemistry and Photobiology, 2019) https://onlinelibrary.wiley.com/doi/abs/10.1111/php.13140).

SUBSTANTIATION: “reliable information” – Published data on DermaSensor’s ESS and Machine Learning technology shows sensitivity >90% across all skin cancers combined (Rodriguez-Diaz et al (Photochemistry and Photobiology, 2019) https://onlinelibrary.wiley.com/doi/abs/10.1111/php.13140).

CLAIMS #2 - “Smarter clinical choices”

SUBSTANTIATION: DermaSensor’s ESS and Machine Learning technology sensitivity in published data surpasses the sensitivity of naked eye examination for skin cancers, while decreasing the morbidity associated with skin cancers . In a published 2018 meta-analysis physician naked eye sensitivity was greater than 90% in only six of 28 in‐person‐based evaluations and physician experience may influence accuracy. (“Diagnosing skin cancer.” Posted December 6, 2018. https://onlinelibrary.wiley.com/doi/abs/10.1111/php.13140).

CLAIM #3 - “DermaSensor is the new, quicker route to better outcomes”

CLAIM #4 - “Enabling early detection using non-invasive spectroscopy”

SUBSTANTIATION: “Quicker” when compared to other technologies that require extensive training, skin preparation and/or image interpretation. "ESS requires no skin preparation and is easy to administer, requiring minimal practitioner training. [It] generates a simple dichotomous output in a non-invasive way." (Rodriguez-Diaz et al (Photochemistry and Photobiology, 2019) https://onlinelibrary.wiley.com/doi/abs/10.1111/php.13140).

SUBSTANTIATION: “route to better outcomes” and "Enabling early detection"– Published data on DermaSensor’s ESS and Machine Learning technology shows sensitivity >90% across all skin cancers combined (Rodriguez-Diaz et al (Photochemistry and Photobiology, 2019). Published data on naked eye examination is variable; in a published 2018 meta-analysis, physician naked-eye sensitivity was greater than 90% in only six of 28 in‐person‐based studies and physician experience may influence accuracy. (“Diagnosing skin cancer.” Posted December 6, 2018. https://www.cochranelibrary.com/collections/doi/SC000033/full ). Therefore, DermaSensor’s technology provides a "route to better outcomes" or "enables early detection" by potentially improving detection of skin cancer. Earlier stages of skin cancer diagnoses have better prognoses. “Skin cancers require early diagnosis and management for optimal outcomes.” https://www.aafp.org/cme/subscriptions/fp-essentials/editions/481-ed.html (Perez LL, Bashline B, Bruner P. Skin Cancer. FP Essent. 2019;481:1-44.)

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