ClinicalTrials.gov
public full text
Public Domain
Validation of Multimodal Evoked Potentials (mmEP) for Predicting Disease Progression in Multiple Sclerosis
Utility of Multimodal Evoked potentials (mmEP) for monitoring disease course and prediction of progression at different stages of Multiple Sclerosis (MS) is investigated
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Endpoint Calibration for a Phase 2 Study of Lisinopril in Multiple Sclerosis#993462
- Standard Model Imaging for Characterizing Multiple Sclerosis Lesion Types: A Lesion-Focused Analysis Compared with Diffusion Tensor Imaging#12996
- Towards Accurate and Reliable ICU Outcome Prediction: A Multimodal Learning Framework Based on Belief Function Theory using Structured EHRs and Free-Text Notes.#170709
- Towards Accurate and Reliable ICU Outcome Prediction: A Multimodal Learning Framework Based on Belief Function Theory using Structured EHRs and Free-Text Notes#164218
- Multimodal Brain Monitoring as a Prognostic Tool for Intracerebral Hemorrhage#1111743
Record · ID 1173149
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive