Project description
New assessment method for Autism Spectrum Disorder
Early diagnosis of children with Autism Spectrum Disorder (ASD) is important, but the current assessment tool, ADOS, is time-consuming. Machine learning could improve screening, but many models are not transparent in their predictions. Supported by the Marie Skłodowska-Curie Actions programme, the CARE-ASD project aims to improve ASD assessment by separating perception from reasoning. It will use machine learning to detect behavioural cues such as gestures and interactions while applying clinical interpretations using the ADOS framework. The project will involve a large-scale dataset annotated with gestures and ADOS items and develop a specialised ML architecture to predict these items. If successful, it will provide clinicians with interpretable decision support tools, thereby reducing assessment delays for children and their families.
Objective
"Autism (ASD) affects 1 in 36 children (2.7%) in the US, with a 700% increase in diagnosis since 1998. Early diagnosis is essential, as interventions during early brain development significantly improve outcomes. However, the current gold-standard assessment, the Autism Diagnostic Observation Schedule (ADOS), is time-consuming, requires expert clinicians, and causes long waits that delay support. Machine learning (ML) can support more scalable and efficient screening, but most existing models rely only on perceptual pattern recognition and act as “black boxes”, generating predictions without explaining how they were reached. This project addresses this limitation by separating perception (ML-based detection of behavioural cues: gestures, attention shifts, interactions) from reasoning (their clinical interpretation within the ADOS framework using clinician-defined rules). This makes the system transparent and clinically meaningful. The main contributions are: (1) the release of a large-scale dataset densely annotated with gestures and ADOS items; (2) a ML architecture that uses specialised ""experts"" in gaze, gesture, and object-use patterns and combine them for gestures and ADOS item prediction; and (3) a clinician-in-the-loop application that displays extracted behaviours and maps them to ADOS scores using symbolic reasoning. The project will be hosted at Inria (France), with clinical collaboration at CHU Nice. I will conduct a secondment at Idiap (Switzerland), where I will train in attention modelling and access a large-scale ASD dataset. If successful, the project will provide clinicians with interpretable decision support tools, improving ASD subtype differentiation and shortening assessment delays that impact children and their families. Moreover, this fellowship gives me a unique opportunity to work with leading experts, collaborate with clinicians, and gain the transferable skills to achieve my goal of building and leading my own research group."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence pattern recognition
- natural sciences computer and information sciences artificial intelligence machine learning
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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(opens in new window) HORIZON-MSCA-2025-PF
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78153 Le Chesnay Cedex
France
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