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Find similar grantsSupports the rigorous clinical validation of candidate biomarkers for neurological and neuromuscular disorders.
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Or search similar grants →According to the current listing, eligibility includes: Not specified, but generally open to research scientists. Confirm the full requirements in the official notice before applying.
Clinical Validation of a Candidate Biomarker for Neurological or Neuromuscular Disorders (U01 Clinical Trial Optional) is funded by National Institute of Neurological Disorders and Stroke (NINDS) - NIH. Verify program details on the funder's official page before applying.
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The DIGITAL-2026-AI-PILOTING-10-SCREENING call under the EU Digital Europe Programme supports the development and piloting of scalable cloud-based AI and Generative AI systems for medical image screening in real-world healthcare settings. Projects must deploy trustworthy European algorithms trained and validated on massive patient datasets, focusing specifically on cancer and cardiovascular disease detection, prevention, and early diagnosis. The programme requires large-scale validation across multiple healthcare settings with human-in-the-loop validation by qualified medical professionals. All projects must comply with the EU AI Act, relevant cybersecurity frameworks, and data protection rules including GDPR, and must prepare Health Technology Assessment (HTA) documentation. Solutions must be interoperable with existing health IT infrastructure including EHR, PACS, and RIS systems. This call is part of the broader GenAI4EU initiative investing nearly EUR 700 million in European generative AI capabilities.
Under the European Commission's GenAI4EU initiative and the Digital Europe Programme, this call (DIGITAL-2026-AI-PILOTING-10-SCREENING) supports the development, deployment, and large-scale clinical validation of cloud-based AI systems for medical image screening across European hospital networks. Funded projects will integrate AI diagnostic tools into routine clinical workflows for cancer (mammography, lung CT, dermatology, pathology) and cardiovascular imaging, establish multi-country networks of AI-powered screening centres, demonstrate clinical performance on large patient datasets, address EU AI Act and MDR compliance, and deliver health-economic evidence to support reimbursement and scale-up. Cybersecurity, data protection under GDPR, and federated learning architectures for cross-border data governance are emphasized.
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