ArticleNeurology (E-Cronicon)2016
Identifying Key Symptoms Differentiating Myalgic Encephalomyelitis and Chronic Fatigue Syndrome from Multiple Sclerosis.
Article in Neurology (E-Cronicon), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review.BMC medical informatics and decision making · 2022Pooled it
- Two neurocognitive domains identified for patients with myalgic encephalomyelitis/chronic fatigue syndrome and post-acute sequelae of COVID-19.Frontiers in neurology · 2025Article
- Artificial intelligence in autoimmune diseases: a bibliometric exploration of the past two decades.Frontiers in immunology · 2025Review
- The Head-Up Tilt Table Test as a Measure of Autonomic Functioning among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.Journal of personalized medicine · 2024Article
- IgG Antibody Responses to Epstein-Barr Virus in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Their Effective Potential for Disease Diagnosis and Pathological Antigenic Mimicry.Medicina (Kaunas, Lithuania) · 2024Article
- Article
- Evaluating case diagnostic criteria for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): toward an empirical case definition.Disability and rehabilitation · 2023Article
- Symptom-based clusters in people with ME/CFS: an illustration of clinical variety in a cross-sectional cohort.Journal of translational medicine · 2023Article
- ME/CFS and Post-Exertional Malaise among Patients with Long COVID.Neurology international · 2022Article
- Differences in Symptoms among Black and White Patients with ME/CFS.Journal of clinical medicine · 2022Article
- Orthostatic intolerance and neurocognitive impairment in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).Epidemiologic methods · 2022Article
- COVID-19 Symptoms Over Time: Comparing Long-Haulers to ME/CFS.Fatigue : biomedicine, health & behavior · 2021Article
- Peripheral endothelial dysfunction in myalgic encephalomyelitis/chronic fatigue syndrome.ESC heart failure · 2020Article
- A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases.NPJ digital medicine · 2020Review
- The development of a short form of the DePaul Symptom Questionnaire.Rehabilitation psychology · 2019Article
- Differentiating Post-Polio Syndrome from Myalgic Encephalomyelitis and Chronic Fatigue Syndrome.Fatigue : biomedicine, health & behavior · 2019Article
- The DePaul Symptom Questionnaire-2: A Validation Study.Fatigue : biomedicine, health & behavior · 2019Article
- Myalgic encephalomyelitis and chronic fatigue syndrome case definitions: effects of requiring a substantial reduction in functioning.Fatigue : biomedicine, health & behavior · 2019Article
- Operationalizing Substantial Reduction in Functioning Among Young Adults with Chronic Fatigue Syndrome.International journal of behavioral medicine · 2018Article
- The Development of the DePaul Symptom Questionnaire: Original, Expanded, Brief, and Pediatric Versions.Frontiers in pediatrics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
It is unclear what key symptoms differentiate Myalgic Encephalomyelitis (ME) and Chronic Fatigue syndrome (CFS) from Multiple Sclerosis (MS). The current study compared self-report symptom data of patients with ME or CFS with those with MS. The self-report data is from the DePaul Symptom Questionnaire, and participants were recruited to take the questionnaire online. Data were analyzed using a machine learning technique called decision trees. Five symptoms best differentiated the groups. The best discriminating symptoms were from the immune domain (i.e., flu-like symptoms and tender lymph nodes), and the trees correctly categorized MS from ME or CFS 81.2% of the time, with those with ME or CFS having more severe symptoms. Our findings support the use of machine learning to further explore the unique nature of these different chronic diseases.
Indexed as
Identifiers
28066845PMC5214344What 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.