Evidence map›Paper›PMID 41039324›Full record

ArticleBMC pediatrics2025

Construction and validation of an automated time label segmentation method for infant cries.

Qiongfang Cao, Min Huang, Xiuju Zhu, Yuling Duan, Qicheng Shu, Xi Huang, Xun Guo, Fangfagn Liu, Ziyu Hua, Fan Xu

Erratum issuedAbstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

10 authors.

Qiongfang Cao *Department of Evidence-based Medicine and Social Medicine, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, 610500, China.
Min Huang *Sichuan Provincial Key Laboratory of Philosophy and Social Sciences for Intelligent Medical Care and Elderly Health Management, Chengdu Medical College, Chengdu, Sichuan, 610500, China.
Xiuju Zhu *Department of Neonatology, Chongqing Medical University Affiliated Children Hospital, Chongqing, 410000, China.
Yuling DuanDepartment of Clinical Medicine, Chengdu Medical College, Sichuan, 610500, China.
Qicheng ShuDepartment of Clinical Medicine, Chengdu Medical College, Sichuan, 610500, China.
Xi HuangDepartment of Art, Art College, Southwest Minzu University, Sichuan, 610041, China.
Xun GuoDepartment of Clinical Medicine, Chengdu Medical College, Sichuan, 610500, China.
Fangfagn LiuDepartment of Art, Art College, Southwest Minzu University, Sichuan, 610041, China.
Ziyu HuaDepartment of Neonatology, Chongqing Medical University Affiliated Children Hospital, Chongqing, 410000, China. h_ziyu@163.com.
Fan XuDepartment of Evidence-based Medicine and Social Medicine, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, 610500, China. xufan@cmc.edu.cn.

Funding

Chengdu Medical College 2023 national and provincial college students innovation and entrepreneurship training program project S202313705056，S202313705053&S202313705047Chengdu Medical College Graduate Student Innovation Research Fund YCX2023-01-41Key Discipline Project at the School of Public Health, Chengdu Medical College No. 21National Key R&D Program of China NO.2023YFE0108400School joint funding 23LHPDZYB08Sichuan applied psychology research centre, CSXL-24215Sichuan Provincial Administration of Traditional Chinese Medicine 2023MS100Sichuan Provincial Key Laboratory of Nursing HLKF2023(F)-1Sichuan Provincial Key Research Base of Social Sciences; Sichuan Research Center for Applied Psychology CSXL-23202Technological Innovation and Applied Development Project of Science and Technology Bureau of Chongqing grants CSTB2022TIAD-KPX0147
6 · The paper itself

Abstract

Infant cries serve as critical indicators of an infant's physiological and psychological states, holding essential clinical value in distinguishing between normal and pathological conditions during early development. However, most studies on infant cries failed to segment between inhalation and exhalation during the crying analysis because segmentation remains great challenge. Therefore, we developed an audio data analysis tool capable of accurately segmenting inhalation and exhalation phases in infant cries, followed by extraction of the duration, frequency, and intensity parameters of each segment. Here, 226 sound clips of infants' cries were collected and analyzed. The results revealed the significant differences in sound parameters between premature and term infants. The whole process allows automatic identification and digital collection of infant cries, and it provides an objective method to evaluate the significance behind the cries.

Indexed as

CryingFemaleHumansInfantInfant, NewbornInfant, PrematureMaleAudio data analysis toolCryPremature infantSegmentTerm infant

Identifiers

PMID41039324
PMCPMC12492842

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Registered trials

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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.