Evidence map›Paper›PMID 42198994›Full record

ArticleAmerican journal of men's health

Impact of Artificial Intelligence, Health Expenditure and Digital Financial Inclusion on Life Expectancy.

Hong Zhang, Qiaoping Shao, Ijaz Uddin, Xiaolan Zhang

Abstract read
In one paragraph

Article in American journal of men's health. 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

4 authors.

Hong ZhangSchool of Business, Jinggangshan University, Ji'an, China.
Qiaoping ShaoShaoxing Central Hospital Huashe Branch, Shaoxing, China.
Ijaz UddinDepartment of Economics, Abdul Wali Khan University, Mardan, Pakistan.
Xiaolan ZhangThe First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Chinese government has actively promoted artificial intelligence (AI) in health care, with momentum building in 2016 through the Healthy China 2030 Initiative. This reform plan aims to modernize health care infrastructure, reduce the burden of chronic diseases, and expand access to medical services in rural areas using digital technologies such as AI. Health expenditure (HE) and digital financial inclusion (DFI) play a crucial role in improving health outcomes. HE improves access to medical services and the quality of care, while DFI allows individuals to afford health care, save for emergencies, and manage health-related financial risks. Therefore, this study examines the impact of AI, health expenditure and DFI on life expectancy (LE) in China from 2013Q1 to 2023Q4. This study employed autoregressive distributed lag (ARDL) and quantile regression analyses to ensure the robustness of the results. The finding shows that gross domestic product (GDP), AI, health expenditure, DFI and government effectiveness have positive effect on LE. This study recommended that the government expand AI integration in health care to improve diagnostics and treatment efficiency. It also emphasized promoting DFI to help low-income groups access health care and manage medical expenses. As well, the study suggested increasing public health expenditure to enhance health care infrastructure and service quality, ultimately improving LE.

Indexed as

Artificial IntelligenceHealth ExpendituresLife ExpectancyChinaDigital HealthHumansMaleARDLartificial intelligenceChinafinancial inclusionhealth expenditurelife expectancy

Identifiers

PMID42198994
PMCPMC13219865

What OpenQuestion holds

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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.