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Developing Machine Learning Classifier Models for Eye Movements to Diagnose Major Psychiatric Disorders

Objective

1 in 5 of us are affected by mental illness during our lifetime. It is the largest cause of disability worldwide costing the global economy a staggering US$2.5 trillion per annum and rising to US$6 trillion per annum by 2030. Although illness specific treatments are available, doctors are struggling to provide accurate and timely diagnosis with misdiagnosis occurring more than half the time. Currently, when patients’ history, symptoms and behaviour don’t meet the criteria set out in the diagnostic manual, it may take up to 10 years to diagnose the illness. And unlike in other branches of medicine there are no objective tests in psychiatry to aid the diagnostic process. SaccScan is a novel point-of-care (PoC) software diagnostic system which has been demonstrated to detect schizophrenia with better than 95% accuracy and can be extended with the same precision to other major psychiatric conditions. The software diagnostic tool successfully utilises eye-movement abnormalities as clinical diagnostic biomarkers for serious mental illnesses. The test can be performed within 30 minutes in a standard consulting room environment and results produced over the internet at near realtime speed. Early economic modelling showed that introducing SaccScan into health care services could produce savings of €33 474 per patient in the case of suspected schizophrenia. The purpose of this SME Innovation Associate application is to identify a post-doctoral talent from across the EU to help develop next generation models within the SaccScan diagnostic system in order to increase the clinical utilities of the test by the identification and implementation of new eye movement biomarkers which in turn will extend the test to other illness categories.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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CSA - Coordination and support action

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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-INNOSUP-2016-2017

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Coordinator

SACCADE DIAGNOSTICS LIMITED
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.

€ 121 250,00
Address
2 LISTER SQUARE
EH3 9GL EDINBURGH
United Kingdom

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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
Scotland Eastern Scotland Edinburgh
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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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.

€ 121 250,00
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