ASPIRE Project

A User-Centered Platform with Modular AI Agents for Literature-Grounded Neuroimaging in Parkinson's Disease.

Project Overview

The ASPIRE project is a five-year plan to establish a new AI research group in Lower Saxony. The group's mission is to develop a novel, user-centric platform that solves a critical bottleneck in clinical neuroscience: the failure of most neuroimaging biomarkers for Parkinson's Disease (PD) to translate into practice due to poor reliability and interpretability.

ASPIRE's innovation is a modular, AI-powered system that empowers researchers to conduct robust, literature-grounded analyses on their own, often small, datasets. The diagram below illustrates the complete ecosystem.

Researcher Agentic PlatformAnalystTheoristCoder AI AssetsKnowledge GraphsFoundational Models

The Challenge of Reliable Biomarkers

Replicability in PD Neuroimaging

Finding Heterogeneity

The scientific literature contains highly variable and contradictory findings, making it difficult to identify consistent biomarker signals.

Small Sample Sizes

Clinical studies often lack sufficient data for training robust AI models, leading to results that are not generalizable.

The Credibility Gap in Medical AI

The "Black Box" Problem

The internal workings of complex AI models are often opaque, creating a major barrier to clinical trust and regulatory approval.

Lack of Domain Knowledge

General-purpose AI models lack the specialized knowledge for nuanced medical tasks, leading to unreliable outputs.