ArticleEuropean journal of neurology2025
Scoping review of clinical decision support systems for multiple sclerosis management: Leveraging information technology and massive health data.
Article in European journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- PRIMUS: a precision medicine platform reusing clinical trials and registry data to support treatment selection in multiple sclerosis.JAMIA open · 2026Article
- Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint.JMIR medical informatics · 2025Article
- From implementation to discontinuation: multi-year experience with the multiple sclerosis performance test as a digital monitoring tool.Frontiers in digital health · 2025Article
- Scoping review of clinical decision support systems for multiple sclerosis management: Leveraging information technology and massive health data.European journal of neurology · 2025Article
- Large language models as clinical decision-support tools in multiple sclerosis and neuromyelitis optica spectrum disorders: A comparative study of ChatGPT-4o and neurologists.Multiple sclerosis journal - experimental, translational and clinicalArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
background and purposeMultiple sclerosis (MS) is a complex autoimmune disease of the central nervous system, with numerous therapeutic options, but a lack of biomarkers to support a mechanistic approach to precision medicine. A computational approach to precision medicine could proceed from clinical decision support systems (CDSSs). They are digital tools aiming to empower physicians through the clinical applications of information technology and massive data. However, the process of their clinical development is still maturing; we aimed to review it in the field of MS.
methodsFor this scoping review, we screened systematically the PubMed database. We identified 24 articles reporting 14 CDSS projects and compared their technical and software development aspects.
resultsThe projects position themselves in various contexts of usage with various algorithmic approaches: expert systems, CDSSs based on similar patients' data visualization, and model-based CDSSs implementing mathematical predictive models. So far, no project has completed its clinical development up to certification for clinical use with global release. Some CDSSs have been replaced at subsequent project iterations. The most advanced projects did not necessarily report every step of clinical development in a dedicated article (proof of concept, offline validation, refined prototype, live clinical evaluation, comparative prospective evaluation). They seek different software distribution options to integrate into health care: internal usage, "peer-to-peer," and marketing distribution.
conclusionsThis review illustrates the potential of clinical applications of information technology and massive data to support MS management and helps clarify the roadmap for future projects as a multidisciplinary and multistep process.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.