Evidence map›Paper›PMID 31724891›Full record

Trial reportAnnals of medicine

Deep learning-based automatic blood pressure measurement: evaluation of the effect of deep breathing, talking and arm movement.

Fan Pan, Peiyu He, Fei Chen, Xiaobo Pu, Qijun Zhao, Dingchang Zheng

Open access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Annals of medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 24% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Survey and Evaluation of Hypertension Machine Learning Research.Journal of the American Heart Association · 2023
    Article
  3. Article
  4. 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

6 authors at 3 institutions in 2 countries.

Fan PanCollege of Electronics and Information Engineering, Sichuan University, Chengdu, China.ORCID 0000-0001-9119-7387
Peiyu HeCollege of Electronics and Information Engineering, Sichuan University, Chengdu, China.
Fei ChenDepartment of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
Xiaobo PuDepartment of Cardiology, West China Hospital, Sichuan University, Chengdu, China.
Qijun ZhaoCollege of Computer Science, Sichuan University, Chengdu, China.
Dingchang ZhengResearch Centre of Intelligent Healthcare, Faculty of Health and Life Science, Coventry University, Coventry, UK.
Sichuan University · CNIntelligent Health (United Kingdom) · GBSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Blood PressureBlood Pressure DeterminationDeep LearningAdultAgedAutomationFemaleHealthy VolunteersHumansMaleMiddle AgedMovementSpeechYoung AdultBlood pressure measurementdeep learningmanual auscultatory methodmeasurement condition

Identifiers

PMID31724891
PMCPMC7877882
OpenAlexW2989241935

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.