Aiforia

Overview
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Clinical Decision Support Systems?
Product stageSegments
Expansion
?
Diagnostic support
?

Aiforia is a pioneering company that provides a cloud-based platform for artificial intelligence (AI)-powered image analysis in pathology and other medical fields. Their cutting-edge deep learning technology is designed to enhance the workflow of pathologists, researchers, and clinicians by offering efficient and scalable solutions for analyzing complex medical images.

Aiforia's platform originated from the Finnish Institute for Molecular Medicine (FIMM) at the University of Helsinki, where researchers developed cloud-based microscopy and pathology tools. Founded in 2013 as a spin-off, Aiforia has since established itself as a leader in AI-based image analysis, with over 200 AI models developed for various applications across numerous diseases, including breast cancer, neurodegenerative disorders, and liver diseases.

The company's robust and intuitive platform harnesses the power of deep learning AI to analyze 2D images with high speed, accuracy, and consistency. Users can train AI models tailored to their specific needs using their domain knowledge, without requiring data science expertise. This versatile approach enables new discoveries, clinical support, and highly accurate and consistent data generation.

Aiforia's technology is disease-agnostic and can be applied to any 2D image, making it a valuable tool for researchers, pathologists, radiologists, and healthcare professionals across various medical disciplines.


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Disclaimer: This company profile has been generated using data obtained through automated web searches and advanced generative AI technology. While we strive to ensure the accuracy and reliability of our sources, auto-generated information could be outdated or inaccurate and should be verified independently.
HQ location:
Helsinki FIN
Founded year:
2013
Employees:
51-100
IPO status:
Private
Total funding:
USD 25.2 mn
Last Funding:
USD 15.3 mn (Series B; Jun 2021)
Last valuation:
USD 20.9 mn (Dec 2017)
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