PMID- 31946329
OWN - NLM
STAT- MEDLINE
DCOM- 20200423
LR  - 20200928
IS  - 2694-0604 (Electronic)
IS  - 2375-7477 (Linking)
VI  - 2019
DP  - 2019 Jul
TI  - Machine learning for classification of uterine activity outside pregnancy.
PG  - 2161-2164
LID - 10.1109/EMBC.2019.8857374 [doi]
AB  - The objective of this study was to investigate the use of classification methods 
      by a machine-learning approach for discriminating the uterine activity during the 
      four phases of the menstrual cycle. Four different classifiers, including support 
      vector machine (SVM), K-nearest neighbors (KNN), Gaussian mixture model (GMM) and 
      naive Bayes are here proposed. A set of amplitude- and frequency-features were 
      extracted from signals measured by two different quantitative and noninvasive 
      methods, such as electrohysterography and ultrasound speckle tracking. The 
      proposed classifiers were trained using all possible feature combinations. The 
      method was applied on a database (24 measurements) collected in different phases 
      of the menstrual cycle, comprising uterine active and quiescent phases. The SVM 
      classifier showed the best performance for discrimination between the different 
      menstrual phases. The classification accuracy, sensitivity, and specificity were 
      90%, 79%, 93%, respectively. Similar methods can in the future contribute to the 
      diagnosis of infertility or other common uterine diseases such as endometriosis.
FAU - Bakkes, Tom H G F
AU  - Bakkes THGF
FAU - Sammali, Federica
AU  - Sammali F
FAU - Kuijsters, Nienke P M
AU  - Kuijsters NPM
FAU - Turco, Simona
AU  - Turco S
FAU - Rabotti, Chiara
AU  - Rabotti C
FAU - Schoot, Dick
AU  - Schoot D
FAU - Mischi, Massimo
AU  - Mischi M
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Annu Int Conf IEEE Eng Med Biol Soc
JT  - Annual International Conference of the IEEE Engineering in Medicine and Biology 
      Society. IEEE Engineering in Medicine and Biology Society. Annual International 
      Conference
JID - 101763872
SB  - IM
MH  - Algorithms
MH  - Bayes Theorem
MH  - Female
MH  - Humans
MH  - *Machine Learning
MH  - *Menstrual Cycle
MH  - Normal Distribution
MH  - Support Vector Machine
MH  - Uterus/*physiology
EDAT- 2020/01/18 06:00
MHDA- 2020/04/24 06:00
CRDT- 2020/01/18 06:00
PHST- 2020/01/18 06:00 [entrez]
PHST- 2020/01/18 06:00 [pubmed]
PHST- 2020/04/24 06:00 [medline]
AID - 10.1109/EMBC.2019.8857374 [doi]
PST - ppublish
SO  - Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:2161-2164. doi: 
      10.1109/EMBC.2019.8857374.