Evidence map›Paper›PMID 39398893›Full record

ArticleDigital health

Artificial neural network-based model for sleep quality prediction for frontline medical staff during major medical assistance.

Qingquan Chen, Zeshun Chen, Xi Zhu, Jiajing Zhuang, Ling Yao, Huaxian Zheng, Jiaxin Li, Tian Xia, Jiayi Lin, Jiewei Huang and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digital health. 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
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.

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

15 authors.

Qingquan ChenThe Sleep Disorder Medicine Center of the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
Zeshun ChenThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Xi ZhuThe School of Public Health, Fujian Medical University, Fuzhou, Fujian Province, China.
Jiajing ZhuangThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Ling YaoThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Huaxian ZhengThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Jiaxin LiAnyang University, Anyang, Henan Province, China.
Tian XiaThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Jiayi LinThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, China.
Jiewei HuangThe Graduate School of Fujian Medical University, Fuzhou, Fujian Province, China.
Yifu ZengCyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, Guangdong Province, China.
Chunmei FanThe Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
Jimin FanThe Sleep Disorder Medicine Center of the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.ORCID https://orcid.org/0009-0003-3610-2412
Duanhong SongThe Sleep Disorder Medicine Center of the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
Yixiang ZhangThe Sleep Disorder Medicine Center of the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.ORCID https://orcid.org/0000-0003-2499-5770

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial neural networkCOVID-19machine learningmedical staffSleep quality

Identifiers

PMID39398893
PMCPMC11467980

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.