Cargando…

Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter

BACKGROUND AND AIM: Fetal biparietal diameter (BPD) is a feasible parameter to predict canine parturition date due to its inverted correlation with days before parturition (DBP). Although such a relationship is generally described using a simple linear regression (SLR) model, the imprecision of this...

Descripción completa

Detalles Bibliográficos
Autores principales: Sananmuang, Thanida, Mankong, Kanchanarat, Ponglowhapan, Suppawiwat, Chokeshaiusaha, Kaj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Veterinary World 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167531/
https://www.ncbi.nlm.nih.gov/pubmed/34083927
http://dx.doi.org/10.14202/vetworld.2021.829-834
_version_ 1783701709471612928
author Sananmuang, Thanida
Mankong, Kanchanarat
Ponglowhapan, Suppawiwat
Chokeshaiusaha, Kaj
author_facet Sananmuang, Thanida
Mankong, Kanchanarat
Ponglowhapan, Suppawiwat
Chokeshaiusaha, Kaj
author_sort Sananmuang, Thanida
collection PubMed
description BACKGROUND AND AIM: Fetal biparietal diameter (BPD) is a feasible parameter to predict canine parturition date due to its inverted correlation with days before parturition (DBP). Although such a relationship is generally described using a simple linear regression (SLR) model, the imprecision of this model in predicting the parturition date in small- to medium-sized dogs is a common problem among veterinarian practitioners. Support vector regression (SVR) is a useful machine learning model for prediction. This study aimed to compare the accuracy of SVR with that of SLR in predicting DBP. MATERIALS AND METHODS: After measuring 101 BPDs in 35 small- to medium-sized pregnant bitches, we fitted the data to the routine SLR model and the SVR model using three different kernel functions, radial basis function SVR, linear SVR, and polynomial SVR. The predicted DBP acquired from each model was further utilized for calculating the coefficient of determination (R2), mean absolute error, and mean squared error scores for determining the prediction accuracy. RESULTS: All SVR models were more accurate than the SLR model at predicting DBP. The linear and polynomial SVRs were identified as the two most accurate models (p<0.01). CONCLUSION: With available machine learning software, linear and polynomial SVRs can be applied to predicting DBP in small- to medium-sized pregnant bitches.
format Online
Article
Text
id pubmed-8167531
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Veterinary World
record_format MEDLINE/PubMed
spelling pubmed-81675312021-06-02 Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter Sananmuang, Thanida Mankong, Kanchanarat Ponglowhapan, Suppawiwat Chokeshaiusaha, Kaj Vet World Research Article BACKGROUND AND AIM: Fetal biparietal diameter (BPD) is a feasible parameter to predict canine parturition date due to its inverted correlation with days before parturition (DBP). Although such a relationship is generally described using a simple linear regression (SLR) model, the imprecision of this model in predicting the parturition date in small- to medium-sized dogs is a common problem among veterinarian practitioners. Support vector regression (SVR) is a useful machine learning model for prediction. This study aimed to compare the accuracy of SVR with that of SLR in predicting DBP. MATERIALS AND METHODS: After measuring 101 BPDs in 35 small- to medium-sized pregnant bitches, we fitted the data to the routine SLR model and the SVR model using three different kernel functions, radial basis function SVR, linear SVR, and polynomial SVR. The predicted DBP acquired from each model was further utilized for calculating the coefficient of determination (R2), mean absolute error, and mean squared error scores for determining the prediction accuracy. RESULTS: All SVR models were more accurate than the SLR model at predicting DBP. The linear and polynomial SVRs were identified as the two most accurate models (p<0.01). CONCLUSION: With available machine learning software, linear and polynomial SVRs can be applied to predicting DBP in small- to medium-sized pregnant bitches. Veterinary World 2021-04 2021-04-02 /pmc/articles/PMC8167531/ /pubmed/34083927 http://dx.doi.org/10.14202/vetworld.2021.829-834 Text en Copyright: © Sananmuang, et al. https://creativecommons.org/licenses/by/4.0/Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Sananmuang, Thanida
Mankong, Kanchanarat
Ponglowhapan, Suppawiwat
Chokeshaiusaha, Kaj
Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title_full Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title_fullStr Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title_full_unstemmed Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title_short Support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
title_sort support vector regression algorithm modeling to predict the parturition date of small - to medium-sized dogs using maternal weight and fetal biparietal diameter
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167531/
https://www.ncbi.nlm.nih.gov/pubmed/34083927
http://dx.doi.org/10.14202/vetworld.2021.829-834
work_keys_str_mv AT sananmuangthanida supportvectorregressionalgorithmmodelingtopredicttheparturitiondateofsmalltomediumsizeddogsusingmaternalweightandfetalbiparietaldiameter
AT mankongkanchanarat supportvectorregressionalgorithmmodelingtopredicttheparturitiondateofsmalltomediumsizeddogsusingmaternalweightandfetalbiparietaldiameter
AT ponglowhapansuppawiwat supportvectorregressionalgorithmmodelingtopredicttheparturitiondateofsmalltomediumsizeddogsusingmaternalweightandfetalbiparietaldiameter
AT chokeshaiusahakaj supportvectorregressionalgorithmmodelingtopredicttheparturitiondateofsmalltomediumsizeddogsusingmaternalweightandfetalbiparietaldiameter