Evidence map›Paper›PMID 34765324›Full record

Trial reportIEEE journal of translational engineering in health and medicine2021

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Po-Han Chiang, Melissa Wong, Sujit Dey

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in IEEE journal of translational engineering in health and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 6 pooled it
6.7field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 6 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  4. Does clinical practice supported by artificial intelligence improve hypertension care management? A pilot systematic review.Hypertension research : official journal of the Japanese Society of Hypertension · 2024
    Pooled it
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  18. Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping Review.International journal of environmental research and public health · 2022
    Article
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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

3 authors at 2 institutions in 1 country.

Po-Han ChiangMobile Systems Design LaboratoryDepartment of Electrical and Computer EngineeringUniversity of California at San Diego La Jolla CA 92092 USA.
Melissa WongDepartment of MedicineUniversity of California at San Diego La Jolla CA 92092 USA.
Sujit DeyMobile Systems Design LaboratoryDepartment of Electrical and Computer EngineeringUniversity of California at San Diego La Jolla CA 92092 USA.
University of California San Diego · USUC San Diego Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Machine LearningWearable Electronic DevicesBlood PressureHumansLife StyleSphygmomanometersBlood pressurehypertensionmachine learningpersonalized modelingsmart healthcare

Identifiers

PMID34765324
PMCPMC8577573
OpenAlexW3184579817

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.