Evidence map›Paper›PMID 42005533›Full record

ReviewNPJ artificial intelligence2026

Data-hugging shields proprietary AI models from research that could disprove them.

Anish Karpurapu, Zhicheng Guo, Xiao Hu, Cynthia Rudin

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Anish KarpurapuMedical Scientist Training Program, Duke University School of Medicine, Durham, NC USA.
Zhicheng GuoDepartment of Computer Science, Duke University, Durham, NC USA.
Xiao HuNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA USA.
Cynthia RudinDepartment of Computer Science, Duke University, Durham, NC USA.

Funding

Novel Algorithm and Data Strategies to detect and Predict atrial fibrillation for post-stroke patients (NADSP)R01HL166233 · NHLBI · EMORY UNIVERSITY · PI Xiao Hu · 2023 to 2026
$2.7M
NHLBI NIH HHS R01 HL166233
6 · The paper itself

Abstract

"Data hugging" blocks independent verification of medical AI. Apple claims age estimation with a mean absolute error of 2.9 years using photoplethysmographic (PPG) signals. Given PPG's noise, such accuracy is questionable, raising concerns about other tech companies' claims. Using UK Biobank data, we find this accuracy unreplicable, achieving results only marginally better than predicting mean age. We advocate for curated public benchmark datasets and evaluation platforms to protect the public from unverifiable claims.

Indexed as

CardiologyComputational biology and bioinformaticsHealth careMedical research

Identifiers

PMID42005533
PMCPMC13090122

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.