Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour

Hisham Allahem; Srinivas Sampalli

doi:10.1016/j.imu.2020.100404

Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour

Hisham Allahem, Srinivas Sampalli

Physics and Astronomy

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Original language	English
Article number	100404
Journal	Informatics in Medicine Unlocked
Volume	20
DOIs	https://doi.org/10.1016/j.imu.2020.100404
Publication status	Published - 2020

ASJC Scopus Subject Areas

Health Informatics

Access to Document

10.1016/j.imu.2020.100404

Cite this

@article{34ad020b82c245498f3537ec46fbd4c3,

title = "Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour",

author = "Hisham Allahem and Srinivas Sampalli",

note = "Funding Information: Jouf University in Saudi Arabia has funded this work with the support of the Saudi Cultural Bureau in Canada. The first author appreciates and acknowledges the assistance provided by these organizations. Funding Information: Jouf University in Saudi Arabia has funded this work with the support of the Saudi Cultural Bureau in Canada . The first author appreciates and acknowledges the assistance provided by these organizations. Publisher Copyright: {\textcopyright} 2020 The Author(s)",

year = "2020",

doi = "10.1016/j.imu.2020.100404",

language = "English",

volume = "20",

journal = "Informatics in Medicine Unlocked",

issn = "2352-9148",

publisher = "Elsevier Ltd.",

}

TY - JOUR

T1 - Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour

AU - Allahem, Hisham

AU - Sampalli, Srinivas

N1 - Funding Information: Jouf University in Saudi Arabia has funded this work with the support of the Saudi Cultural Bureau in Canada. The first author appreciates and acknowledges the assistance provided by these organizations. Funding Information: Jouf University in Saudi Arabia has funded this work with the support of the Saudi Cultural Bureau in Canada . The first author appreciates and acknowledges the assistance provided by these organizations. Publisher Copyright: © 2020 The Author(s)

PY - 2020

Y1 - 2020

UR - http://www.scopus.com/inward/record.url?scp=85089522611&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85089522611&partnerID=8YFLogxK

U2 - 10.1016/j.imu.2020.100404

DO - 10.1016/j.imu.2020.100404

M3 - Article

AN - SCOPUS:85089522611

SN - 2352-9148

VL - 20

JO - Informatics in Medicine Unlocked

JF - Informatics in Medicine Unlocked

M1 - 100404

ER -

Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour

ASJC Scopus Subject Areas

Access to Document

Other files and links

Fingerprint

Cite this