ArticleClinical neurophysiology practice2024
E-norms and AI in clinical neurophysiology.
Article in Clinical neurophysiology practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Revisiting the Extrapolated Reference Values (E-Ref) Estimation.Muscle & nerve · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To describe the use of Artificial Intelligence (AI) to automate the e-norms method, a technique used to derive normative data from patient studies, mixed datasets that contain both normal and abnormal data. Multiple studies have shown that normal values collected with the e-norms method compare favorably with those collected from healthy volunteers using traditional methods. Methods: OpenAI's ChatGPT was used by the author to build a Python script to automate the e-norms method's plateau identification, the area of the e-norms curve where a variable's normal values lie. To date, e-norms plateau identification has been done visually using an Excel Macro developed for that purpose. Results: E-norms normal values derived from the visual e-norms plateau identification with the Excel Macro compared favorably with those derived from the OpenAI's Python script developed by the author to automate the e-norms plateau identification. Conclusions: OpenAI's ChatGPT Python scripts can be developed by users with little to no experience in programming to automate the collection of e-norms normal values. Significance: A Neurologist with no experience in programming, and a limited knowledge of statistics was able to develop this on his own without the help of any programmers or statisticians.
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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.