ArticleFrontiers in immunology2025
Artificial intelligence and science of patient input: a perspective from people with multiple sclerosis.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed.
- [XVIII Post-ECTRIMS Meeting: Review of the New Developments Presented at the 2025 ECTRIMS Congress (Part I)].Revista de neurologia · 2026Article
- Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective.PLOS digital health · 2026Article
- The Use of Patient-Reported Outcome Measures in Developmental Age: A Complementary Tool for Pediatric Multiple Sclerosis Prognosis.Neurology and therapy · 2026Review
- Mechanistic Insights into the Role of Artificial Intelligence and Machine Learning in the Diagnosis and Management of Multiple Sclerosis.Pathophysiology : the official journal of the International Society for Pathophysiology · 2026Review
- Available guidance for ethical challenges in learning health systems: an integrative literature review.Health research policy and systems · 2026Review
- Digital patient experience tools in multiple sclerosis: a landscape analysis of the global Patient-Reported Outcomes in Multiple Sclerosis (PROMS) initiative.EClinicalMedicine · 2026Article
- Integrating big data and artificial intelligence to predict progression in multiple sclerosis: challenges and the path forward.Journal of neuroengineering and rehabilitation · 2025Review
- Enhancing patient-reported outcomes in stroke care: a path to improved well-being.Frontiers in neurology · 2025Article
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
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) can play a vital role in achieving a shift towards predictive, preventive, and personalized medicine, provided we are guided by the science with and of patient input. Patient-reported outcome measures (PROMs) represent a unique opportunity to capture experiential knowledge from people living with health conditions and make it scientifically relevant for all other stakeholders. Despite this, there is limited uptake of the use of standardized outcomes including PROMs within the research and healthcare system. This perspective article discusses the challenges of using PROMs at scale, with a focus on multiple sclerosis. AI approaches can enable learning health systems that improve the quality of care by examining the care health systems presently give, as well as accelerating research and innovation. However, we argue that it is crucial that advances in AI - whether relating to research, clinical practice or health systems policy - are not developed in isolation and implemented 'to' people, but in collaboration 'with' them. This implementation of science with patient input, which is at the heart of the Global PROs for Multiple Sclerosis (PROMS) Initiative, will ensure that we maximize the potential benefits of AI for people with MS, whilst avoiding unintended consequences.
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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.