This project addresses the current fragmentation and diagnostic complexity in neurodegenerative disorders by developing a cross‑hospital, data‑driven decision support application that unifies patient information and enhances diagnostic accuracy. It builds a large multimodal dataset from several hospitals, ensures interoperability through standards such as FHIR, SNOMED‑CT and DICOM, and develops state‑of‑the‑art machine‑learning models—augmented with explainable AI—to support clinicians in differentiating disorders and identifying the usefulness of additional tests.