Evidence map›Paper›PMID 42841059›Full record

ArticleNature health2026

PhysioNet As A Global Platform for Biomedical Research.

Tom Pollard, Benjamin Moody, Li-Wei Lehman, Brian Gow, Chrystinne Fernandes, Chen Xie, Alistair Johnson, Roger Mark, Thomas Heldt

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Unlocking Sensitive Data with SPHERE in the Age of AI.bioRxiv : the preprint server for biology · 2026
    Article
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

9 authors.

Tom PollardInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Benjamin MoodyInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Li-Wei LehmanInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Brian GowInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Chrystinne FernandesInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Chen XieInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Alistair JohnsonInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Roger MarkInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Thomas HeldtInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.

Funding

Research Resource for Complex Physiologic SignalsR01EB030362 · NIBIB · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GOLDBERGER, ARY LOUIS · 2020 to 2025
$5.8M
PhysioNet: A FAIR and sustainable data repositoryU24EB037545 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Thomas Heldt, Tom Pollard · 2025 to 2026
$1.8M
NIBIB NIH HHS R01 EB030362NIBIB NIH HHS U24 EB037545
6 · The paper itself

Abstract

PhysioNet (www.physionet.org), a public platform for sharing biomedical and clinical data, has become a foundational resource for data-driven health research. Created in 1999 as an outreach component of an NIH-funded research project to host physiological signals contributed primarily by a team of Boston-area collaborators, it has since grown into a global repository hosting more than 400 published resources and supporting over 190,000 registered users. PhysioNet resources now span physiological waveforms, structured electronic health records, clinical text, imaging data, annotations, and software, providing a common foundation for reproducible research, model benchmarking, regulatory evaluation, and algorithm development in biomedical AI. Over 25 years, these resources have enabled tens of thousands of studies, influenced international standards, and supported education and workforce development worldwide. Here we describe PhysioNet's evolution, assess its scientific and societal impact, and outline future directions for advancing secure data sharing, community engagement, and scalable research infrastructure.

Indexed as

AI for HealthBiomedicinePhysiologyPhysioNetRepository

Identifiers

PMID42841059
PMCPMC13641116

What OpenQuestion holds

Textmetadata
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.