Evidence map›Paper›PMID 36858462›Full record

ArticleBMJ health & care informatics2023

Study of decision tree algorithms: effects of air pollution on under five mortality in Ulaanbaatar.

Akhit Tileubai, Javzmaa Tsend, Bat-Enkh Oyunbileg, Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar, Baatarkhuu Tsagaan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ health & care informatics, 2023. 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. 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.

Akhit TileubaiDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Javzmaa TsendDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia javzmaa.ts@mnums.edu.mn.ORCID http://orcid.org/0000-0002-4369-5549
Bat-Enkh OyunbilegDepartment of Information Technology, School of Information and Telecommunication Technology, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.
Purevdolgor LuvsantserenDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Ajnai Luvsan-IshDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Baasandorj ChilhaasurenDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Jargalbat PuntsagdashDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Galbadrakh ChuluunbaatarDepartment of Physics & Health Informatics, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.
Baatarkhuu TsagaanDepartment of Information Technology, School of Information and Telecommunication Technology, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectives4.2 million people die every year from many diseases due to air pollution. The WHO confirms that 92% of the world's population lives in areas where the air quality limit is exceeded. In 251 days of 2011, the concentration of fine particulate matter in Ulaanbaatar exceeded the permissible level by 62%-76%. According to the results of the research, the content of fine particles decreased by 37%-46% in 2019. Because it is harmful to the health of children, we aimed to show the effect of air pollution on the mortality through data mining.

methodsIn many countries, research is being conducted to generate effective knowledge from big data using data mining methods. So, we are working to introduce this method to the health sector of Mongolia. In this study, we used the decision tree algorithms.

resultsWe collected data on air pollution and under five mortality for 2019-2022 in Ulaanbaatar and created the database, built the models using the algorithms, and compared the results with the Mongolian standard. If the average of PM10 in winter is higher than the concentration specified in the standard, the mortality rate is likely to be high. Mortality is likely to be high if the nitrogen dioxide tolerance is high in the spring.

conclusionThe accuracy of the models calculated by the C5.0 algorithm is higher than the determined by the CART algorithm, the sensitivity and specificity values are higher than 0.50, so the mortality rates are uniformly predicted and low mortality prevails.

Indexed as

Air PollutionAlgorithmsBig DataChildData MiningDecision TreesHumansArtificial intelligenceBMJ Health InformaticsData MiningData Science

Identifiers

PMID36858462
PMCPMC9980318

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.