GEMINI aims to deliver validated multi-organ and multi-scale computational models for treatment decision support and improved fundamental understanding of acute strokes, both ischaemic and haemorrhagic. We will demonstrate the added benefit of these computational models in personalised disease management. Specifically, GEMINI will deliver validated, integrated multi-scale, multi-organ Digital Twin in Healthcare (DTH) models for cerebral blood and cerebrospinal fluid flow, brain perfusion and metabolism, and blood flow and thrombosis along the heart-brain axis by integrating available and newly developed dynamic, interoperable, and modular computational models. Building on these models, GEMINI will deliver validated population-based DTHs of ischemic and haemorrhagic stroke aetiology and onset, treatment, and disease progression. Utilising these population-based DTHs, GEMINI will validate five personalised subject-specific DTHs, (1) stroke treatment, and (2) disease progression DTHs for acute ischaemic stroke and (3) aneurysm treatment, (4) subarachnoid haemorrhage progression, and (5) unruptured intracranial aneurysm risk assessment DTHs for haemorrhagic stroke to guide patient care and long-term management. We will bring proof of value of digital twins by the evaluation of the ischaemic stroke treatment selection DTH in a multi-centre clinical trial, in which treatment and patient outcomes are compared in situations with and without the availability of a DTH. GEMINI will implement a project-wide structured approach for data harmonisation, curation, model validation, verification, and model certification of the DTHs. Several outcomes of GEMINI have a high value for clinical practice, medical device industry, and in enhancing research in the fields of (bio)medical and computer sciences, warranting an extensive valorisation strategy with adequate IP protection and versatile exploitation actions to enhance a wide adaptation of the results of GEMINI.

SHERPA will empower interventional radiologists (IR), an overburdened group of specialists who use medical imaging and image-guided devices to perform complex, high-risk interventions. Since trust in technology is rooted in relationships – not in a technical specification or feature, AI-powered assistive technologies will be delivered as a seamless, trusted companion (a ‘sherpa’) across the workflow for two clinical domains (Neurology and Oncology), validated with IR and patients through seven clinical studies, and made available to other medical specialities through a framework methodology and outreach to the entire IR community. The automated workflows and their benefits at user, patient and system levels will be evaluated for two clinical applications: 1. Minimally invasive neurovascular interventions (brain aneurysms) and 2. Minimally invasive interventional oncology (liver tumour ablations). Fueled by cutting-edge advances in AI and robotics yet profusely human-centric, workflow automation will minimise the risk of errors and inconsistencies, ensuring the accuracy and reliability of clinical decisions and boosting IR confidence and job satisfaction. As repetitive, time-consuming tasks can be performed automatically, the IR will gain the much-needed relief to focus on the intervention and the interaction with the patient; the expertise threshold will be decreased, improving workload distribution and team dynamics. Through generalising principles and methodological framework, the insights from SHERPA will extend their benefits to other medical specialties dealing with complex workflows and critical decision-making.