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Deep learning AI in cancer diagnostics

Project description

Introduction of AI-based cloud platform for cancer diagnostics

A growing ageing population and high cancer rates result in an ever increasing number of clinical samples. There is urgent need for a user-friendly affordable tool to streamline the workflow and data access for pathologists, providing them with automated and objective analyses. The EU-funded AiforCancerDX project provides support for clinical introduction of the Aiforia® Cloud platform. The platform has been built by Aiforia Technologies Oy by a team of experts in medicine, business and software development, and is based on deep-learning AI software. The Aiforia® Cloud is already used by more than 50 organisations for research purposes. The project will develop this platform for clinical applications creating deep-learning algorithms for automated cancer diagnostics.

Objective

Aging populations and increasing cancer rates are increasing the number of samples in healthcare. Despite the growing trend of digitalisation, pathologists are still reviewing the samples manually, which is a subjective, time-consuming, expensive manual process that exposes patients to the risk of misdiagnosis. Thus, there is a clear need for an affordable tool that supports and streamlines the workflows of pathologist, complementing humans with automated and objective analysis.

Aiforia® Cloud platform augments the efficiency and consistency of a pathologist’s clinical workflow. It removes the slow and inconsistent manual work by automatically performing a range of laborious image analysis tasks, in a fraction of time with unprecedented accuracy and consistency. The productivity leap is enabled by our deep learning AI software, implemented on a cloud platform, and developed specifically for pathology. The platform has been built by Aiforia Technologies Oy, a Finnish SME, bringing together a team of experts in medicine, business, and software development.

The award-winning Aiforia® Cloud is already used by more than 50 organisations for research purposes. With the AiforCancerDx project, the platform will be introduced to clinical use. We will build the world’s first ready-made deep learning algorithms for automated cancer diagnostics. The project allows Aiforia Technologies to remain at the forefront of the digital revolution of pathology and capture a significant share of the global market expected to grow to €900 million by 2020.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

SME - SME instrument

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-EIC-SMEInst-2018-2020

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Coordinator

AIFORIA TECHNOLOGIES OYJ
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 051 000,00
Address
PURSIMIEHENKATU 29-31 D 610
00150 Helsinki
Finland

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Manner-Suomi Helsinki-Uusimaa Helsinki-Uusimaa
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 930 000,00
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