ArticleAnimals : an open access journal from MDPI2022
Improving Ovine Behavioral Pain Diagnosis by Implementing Statistical Weightings Based on Logistic Regression and Random Forest Algorithms.
Article in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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.
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Who cites it
9 citing papers in PubMed.
- Objective assessment of acute pain in foals using a facial expression-based pain scale.Equine veterinary journal · 2025Article
- Proposing a short version of the Unesp-Botucatu pig acute pain scale using a novel application of machine learning technique.Scientific reports · 2025Article
- Advancing outcome measure development and analytical approaches: Pain in Animals Workshop 2023.Frontiers in pain research (Lausanne, Switzerland) · 2025Review
- Clinical validation of the Unesp-Botucatu acute pain scale in sheep undergoing orthopedic surgery.PloS one · 2025Article
- Application of Machine Learning in Predicting Perioperative Outcomes in Patients with Cancer: A Narrative Review for Clinicians.Current oncology (Toronto, Ont.) · 2024Review
- Simplified assessment of castration-induced pain in pigs using lower complexity algorithms.Scientific reports · 2023Article
- Development and Validation of the Unesp-Botucatu Goat Acute Pain Scale.Animals : an open access journal from MDPI · 2023Article
- Reliability and Validity of UNESP-Botucatu Cattle Pain Scale and Cow Pain Scale inAnimals : an open access journal from MDPI · 2023Article
- Validation of the Unesp-Botucatu pig composite acute pain scale (UPAPS) in piglets undergoing castration.PloS one · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Recently, the Unesp-Botucatu sheep acute pain scale (USAPS) was created, refined, and psychometrically validated as a tool that offers fast, robust, and simple application. Evidence points to an improvement in pain diagnosis when the importance of the behavioral items of an instrument is statistically weighted; however, this has not yet been investigated in animals. The objective was to investigate whether the implementation of statistical weightings using machine learning algorithms improves the USAPS discriminatory capacity. A behavioral database, previously collected for USAPS validation, of 48 sheep in the perioperative period of laparoscopy was used. A multilevel binomial logistic regression algorithm and a random forest algorithm were used to determine the statistical weights and classify the sheep as to whether they needed analgesia or not. The quality of the classification, estimated by the area under the curve (AUC) and its 95% confidence interval (CI), was compared between the USAPS versions. The USAPS AUCs weighted by multilevel binomial logistic regression (96.59 CI: [95.02-98.15];
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Registered trials
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.