Evidence map›Paper›PMID 35936542›Full record

ArticleIranian journal of public health2022

Stroke Risk Assessment and Emergency Mobile Application in a Hospital in Thailand.

Siwipa Pruitikanee, Jinda Kongcharoen, Supattra Puttinaovarat, Thotsaphon Yaifai, Sasikorn Chaitada

Open access · goldAbstract read
In one paragraph

Article in Iranian journal of public health, 2022. 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, top 95% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Siwipa PruitikaneeFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand.
Jinda KongcharoenFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand.
Supattra PuttinaovaratFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand.
Thotsaphon YaifaiFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand.
Sasikorn ChaitadaFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand.
Prince of Songkla University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cerebrovascular diseases or stroke tend to cause high mortality in Thailand. An essential responsibility of a hospital is the development of medical care to support the safety of patients. For this purpose, a smartphone application was developed for the risk assessment and emergency system for stroke treatment in a hospital in Thailand. Methods: The proposed application involved the risk assessment related to the occurrence of stroke evaluated by the health status and face image using analytical geometry and face detection technology. The social network Application Programming Interface (API), LINE Notify API, and Global Positioning System (GPS) were used to inform the Stroke team in the Suratthani hospital about emergency cases, followed their requirement in 2020. Results: From the testing, the facial angulation classification, calculated using a support vector machine (SVM), had 92.38% accuracy. The system also provided an emergency call and text messaging that includes patient's current location and personal information to the stroke team directly, which gave an opportunity for the patient to receive treatment quickly. Conclusion: The emergency system can help quickly perform the risk assessment of stroke. Our proposed system provides automated management.

Indexed as

ApplicationFace detectionScreeningStrokeSupport vector machine

Identifiers

PMID35936542
PMCPMC9288415
OpenAlexW4224264604

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.