Evidence map›Paper›PMID 42774266›Full record

ArticleCureus2026

External Validation, Reproducibility, and Interoperability in Digitized Traditional Diagnostic Research: A Cross-Sectional Content Analysis.

Ankit Srivastava, Vandita Srivastava

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ankit SrivastavaHomeopathy, Dr. Ankit Srivastava Homeopathic Clinic, Gorakhpur, IND.
Vandita SrivastavaDepartment of Sanskrit, Banaras Hindu University, Varanasi, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional diagnostic research increasingly uses digital imaging, physiological signals, omics, and machine learning. Technical performance alone, however, does not establish that a method is independently validated, reproducible, or ready for clinical data integration. This study quantified the translational safeguards reported in published human studies of digitized traditional diagnostic phenotypes and signals.

methodsWe conducted a secondary cross-sectional content analysis of a predefined literature library assembled through a documented PubMed and Lens/Scopus search and screening process for a separate scoping-review project and indexed from 2000 through July 4, 2026. This was not a de novo systematic review. From the broader 195-record library, 100 formed the complete source-verifiable analysis frame because all prespecified validation, reproducibility, and interoperability outcomes could be determined from accessible source material at the audit cutoff. Records were not selected according to whether any safeguard was present or absent. Two reviewers evaluated eligibility and prespecified safeguards; 12 content exclusions left 88 eligible studies. We calculated proportions with Wilson 95% confidence intervals (CI) and an explicitly nested clinical-translation cascade.

resultsInternal validation was reported in 51 of 88 studies (58.0%; 95% CI 47.5%-67.7%), whereas eight used an independent external cohort (9.1%; 95% CI 4.7%-16.9%). Prospective clinical evaluation was reported in 10 studies (11.4%), longitudinal outcome validation in two (2.3%), calibration in eight (9.1%), and clinical utility assessment in two (2.3%). Public datasets, analytical code, and accessible trained models were available in 13 (14.8%), three (3.4%), and two (2.3%) studies, respectively. No included study explicitly reported clinical terminology or ontology mapping, electronic health record compatibility, or Fast Healthcare Interoperability Resources mapping. The cumulative cascade was 88 eligible studies, 52 with any internal or external validation, eight with independent external validation, two also prospectively or longitudinally evaluated, one also providing a reusable resource, and none reaching interoperability.

conclusionAmong the 88 eligible source-verifiable studies included in this complete-case analysis, technical validation was substantially more frequently reported than independent external validation, longitudinal clinical evaluation, reusable code or models, or documented interoperability. These findings characterize the analyzed source-verifiable literature and should not be interpreted as prevalence estimates for the broader 195-record parent library or the field as a whole. Future work should prioritize independent cohorts, clinically meaningful follow-up, reusable research resources, and standardized clinical data representation.

Indexed as

clinical phenotypingdigital healthelectronic health recordsexternal validationhealth datainteroperabilitymachine learning (ml)research reproducibilitytraditional medicine

Identifiers

PMID42774266
PMCPMC13593928

What OpenQuestion holds

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Registered trials

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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.