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AISC
Melatech is partner of the AISC research consortium. AISC (AI-augmented training and feedback in Skin Cancer diagnostics) aims to investigate how artificial intelligence can improve the training of healthcare professionals in skin cancer diagnostics through the Dermloop platform.
The consortium includes 28 researchers across eight world-leading research institutions in Denmark, Norway, and Australia. It is funded by Innovationsfonden, the Danish Cancer Society and the Capital Region of Denmark.
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illustration: globus of dermoscopic images
Publications
Gustav Gede Nervil et al, 2024
​​Teledermoscopic triage of melanoma-suspicious skin lesions is safe: A retrospective comparative diagnostic accuracy study with multiple assessors
Gustav Gede Nervil et al, 2023
Improving Skin Cancer Diagnostics Through a Mobile App With a Large Interactive Image Repository: Randomized Controlled Trial
Niels Kvorning Ternov et al, 2022
Generalizability and usefulness of artificial intelligence for skin cancer diagnostics: An algorithm validation study
Niels Kvorning Ternov et al, 2020
Reliable test of clinicians’ mastery in skin cancer diagnostics
illustration: globus of dermoscopic images
AISC-DAH Trial
The Dermoscopic Augmented Histology Trial (DAHT) investigates how dermoscopy training impacts pathologists' diagnoses by providing them with patient information, clinical images, and dermoscopic images during histopathological analysis. Half of the participating pathologists will also have access to Dermloop Learn, our AI-based learning tool. The study aims to foster collaboration between pathologists and other specialists involved in skin cancer diagnostics.
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SynTia
Synergistic, Transparent and Interpretable Artificial intelligence in Skin Cancer Diagnostics
The SynTIA research project aims to revolutionize teledermatology by developing an AI system that provides dermatologists with faster, more accurate and interpretable assessments of suspicious skin lesions.
The project focuses on delivering AI-driven diagnostic feedback, predicting lesion progression over 3-6 months and analyzing clinician biases to reduce misdiagnoses. SynTia includes data from the AISC database and Dermloop Learn and integrates machine learning on the Dermloop.
With an investment of 11.6 million DKK from Innovationsfonden, SynTIA has the potential to set new standards for virtual skin cancer diagnostics and improve patient outcomes.
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Collaborators
  • Melatech
  • Danmarks Tekniske Universitet
  • Copenhagen Academy for Medical Education and Simulation (CAMES)
  • Herlev Hospital
  • Odense Hospital
PRSONAL
The PRSONAL research project aims to personalize breast cancer screening in Denmark by assessing individual risk factors, allowing high-risk women to be screened more frequently while reducing unnecessary mammograms for low-risk women. Involving more than 200,000 women, the project tailors mammography screening by assessing lifestyle factors, family history and breast tissue density.
PRSONAL is conducted at the Mammography Clinic at Gentofte Hospital in Region Hovedstaden in in collaboration with Region Hovedstaden, the Clinical Biochemistry Department at Herlev and Gentofte Hospital and the Danish Cancer Society (Kræftens Bekæmpelse).
Melatech contributed to PRSONAL by building a tool for risk communication. (maybe more info)?
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