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EU project Microb-AI-ome starts on April 1st 2023
Integrating AI in Stroke Neurorehabilitation
Coordinated by Prof. Jan Baumbach, Institute for Computational Systems Biology, Universität Hamburg (DE), project management by tp21.
Duration: 5 years - Start: 01 April 2023 - Total funding: approximately € 6 million.
Vision...
In the EU, 1 in 35 women and 1 in 23 men will be diagnosed with colorectal cancer (CRC) in their life span (ca. 340,000
cases and 156,000 deaths in 2020) causing an annual economic burden of ca. 20 billion EUR. Identifying CRC early
enables better treatment options. Screening usually entails a quantitative faecal immunological test (FIT) to predict the
need of colonoscopy for the detection of colorectal lesions, an expensive and invasive procedure. We aim to predict
this need with specificity increased by >20 percentage points by using metagenomic microbiomes. We hypothesise
that computational microbiome profiles extracted using artificial intelligence (Al) technology will allow for optimised
personal therapy stratification. However, clinicians do not have access to broad microbiome data. With Microb-AIome,
we will develop a novel kind of computational stratification technology to enable microbiome-enhanced precision
medicine of CRC. Metagenomic microbiome data to date is distributed over many national registries, and privacy
regulations are hindering its effective integration. With Microb-AI-ome, we will overcome this barrier by establishing the
first privacy-preserving federated big data network in CRC research. We will integrate isolated, national databases into
one international federated database network - rather than a cloud - covering metagenomes for over 5,000 individuals
screened for CRC, and an expected total of 100,000 by 2026. Microb-AI-ome ensures that no sensitive patient data will
leave the safe harbours of the local databases while still allowing for the classification of clinical CRC phenotypes, which
we will demonstrate in clinical practice allowing regulatory bodies to adopt evidence-based guidelines. Our consortium
combines expertise in CRC and its treatment, microbiomics, artificial intelligence, software development, and privacy
protection to close the gap between privacy and big data in international medical research.
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EU project AISN started
Integrating AI in Stroke Neurorehabilitation
Coordinated by Prof. Paul Verschure, STICHTING RADBOUD UNIVERSITEIT (NL), project management by tp21.
Duration: 4 years - Start: 01 December 2022 - Total funding: approximately € 7.8 million.
Vision...
Health services are increasingly moving towards a treatment continuum aligned with the patient journey. This transition will critically depend on the successful deployment of trustworthy AI-enhanced technologies that are accurate, secure, and trusted. The AISN project will develop and validate operating procedures and guidelines for integrating AI in a healthcare continuum, focussing on post-stroke rehabilitation. AISN delivers a representative AI health platform built from integrating validated platforms for data acquisition and access, clinical interpretation, whole-brain simulation, clinically validated intervention delivery and optimization and model-based prediction. The AISN integrated platform will be validated in the clinical context of rehabilitation in the outpatient and at-home phase and facilitate a concrete assessment of the fundamental ways in which AI-enhanced clinical decision-support will change the care pathway and the formulation of novel AI compatible treatment guidelines. AISN ensures an ethical approach by developing legal and ethical guidelines for the robust, fair, and trustworthy deployment of AI in health and validating acceptance and transparency of its solutions. Building on the AISN platform, the project will test current standard operating procedures for integrating AI in health care and formulate and validate new ones where needed. The AISN guidelines and procedures will emphasize the evidence base and safety of clinical interventions, transparency, prognostics at varying time-scales, personalization of interventions, access to disease-specific information by clinicians, patients and their careers, and assure that the potential of AI is fully developed in the service of value-based medicine satisfying standards of security and safety. We will go beyond currently available guidelines and frameworks by emphasizing explainability, AI tools with evolving performance, and the dynamic interaction between users and algorithms.
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EU project CAVAA started
Counterfactual Assessment and Valuation for Awareness Architecture
Coordinated by Prof. Paul Verschure, STICHTING RADBOUD UNIVERSITEIT (NL), project management by tp21.
Duration: 4 years - Start: 01 October 2022 - Total funding: approximately € 3.1 million.
Vision
The Counterfactual Assessment and Valuation for Awareness Architecture (CAVAA) project proposes that awareness serves survival in a world governed by hidden states, to deal with the “invisible”, from unexplored environments to social interaction that depends on the internal states of agents and moral norms. Awareness reflects a virtual world, a hybrid of perceptual evidence, memory states, and inferred “unobservables”, extended in space and time. The CAVAA project will realize a theory of awareness instantiated as an integrated computational architecture and its components to explain awareness in biological systems and engineer it in technological ones. It will realize underlying computational components of perception, memory, virtualization, simulation, and integration, embody the architecture in robots and artificial agents, validate it across a range of use-cases involving the interaction between multiple humans and artificial agents, using accepted measures and behavioural correlates of awareness. Use cases will address robot foraging, social robotics, computer game benchmarks and human-generated decision trees in a health coach. These benchmarks will focus on resolving trade-offs, e.g. between search efficiency and robustness, and assess the acceptance of human users of aware technology. CAVAA’s awareness engineering is accompanied by an ethics framework towards human users and aware artefacts in the broader spectrum of trustworthy AI, considering shared ontologies, intention complementarity, and behavioural matching, an empathy, relevance of outcomes, reciprocity, counterfactuals and projections towards new future scenarios, and to predict the impact of choices. CAVAA will deliver a better user experience because of its explainability, adaptability, and legibility. CAVAA’s integrated framework redefines how we look at the relationship between humans, other species and smart technologies because it makes the invisible visible.
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