Petanux operates across several AI-driven sectors, including medical imaging, digital health, retail analytics, indoor navigation and enterprise automation. For the Korean market, the company’s primary focus is medical and diagnostic AI, particularly DermVision, its solution for structured skin lesi...
Manufactured by
Petanux GmbH
Germany
Petanux operates across several AI-driven sectors, including medical imaging, digital health, retail analytics, indoor navigation and enterprise automation. For the Korean market, the company’s primary focus is medical and diagnostic AI, particularly DermVision, its solution for structured skin lesion assessment and clinical documentation. Petanux’s expertise spans computer vision, deep learning, data pipelines and secure on-premise or private cloud deployments. Key features of its solutions include a modular architecture, robust privacy standards and seamless integration into existing clinical workflows.
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AI Medical Technology AB · Sweden
CE-marked AI-powered clinical decision support application for dermatoscopic image analysis. Delivers automated skin lesion diagnostics within seconds using smartphone-captured dermoscopy images, enabling rapid assessment with high negative predictive value for malignancy exclusion. Reduces diagnostic uncertainty and supports clinicians in primary care and dermatology settings.
SG Healthcare Co., Ltd · South Korea
AI-integrated diagnostic platform enhancing image acquisition quality, analysis, and clinical decision support for radiology centers.
AI Medical Technology AB · Sweden
DermAIM is a cloud-based AI engine delivered via secure APIs that provides clinically validated skin lesion risk assessment for healthcare system vendors and integrated healthcare platforms. It enables healthcare systems to incorporate AI-driven decision support for melanoma assessment into their existing digital infrastructure. The engine utilizes the same clinically validated AI technology as Dermalyser but is designed specifically for system-level integration rather than individual app deployment.
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