Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

308
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
308

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sperm 28S ribosomal RNA fragments as a potential biomarker for embryo quality in in vitro fertilization.

Journal of assisted reproduction and genetics·2026
Same author

Identification of key metabolic enzymes involved in the activation of obeldesivir and remdesivir to the active triphosphate metabolite.

Antimicrobial agents and chemotherapy·2026
Same author

Focused ultrasound in veterinary medicine.

Veterinary journal (London, England : 1997)·2026
Same author

Advances in research and application of therapeutic antibody strategies for porcine rotavirus prevention and control.

Vaccine·2026
Same author

Characteristics of COVID-19 vaccine hesitancy in university students: Methodological insights from a syndemic perspective.

Human vaccines & immunotherapeutics·2026
Same author

Management of Recurrent Orbital Swelling in a Goose: Comment.

Veterinary ophthalmology·2026

Related Experiment Video

Updated: May 14, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.6K

A novel cross-validated machine learning based Alertix-Cancer Risk Index for early detection of canine malignancies.

Hanan Sharif1,2, Reza Arabi Belaghi3, Kiran Kumar Jagarlamudi2

  • 1Alertix Veterinary Diagnostics, Stockholm, Sweden.

Frontiers in Veterinary Science
|May 12, 2025
PubMed
Summary

A new machine learning model, Alertix-Cancer Risk Index (Alertix-CRI), combines canine Thymidine kinase 1 (TK1) and C-reactive protein (cCRP) levels for early tumor detection. This non-invasive biomarker approach significantly improves diagnostic accuracy in dogs.

Keywords:
cCRPcanine TK1 ELISAcanine lymphomagradient boosting algorithmmachine learning modelsmonoclonal antibodyserum TK1 concentrationsolid tumors

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Related Experiment Videos

Last Updated: May 14, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.6K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Area of Science:

  • Veterinary Medicine
  • Biomarker Discovery
  • Machine Learning in Oncology

Background:

  • Growing demand for non-invasive tumor biomarkers in veterinary medicine.
  • Thymidine kinase 1 (TK1) is a known proliferation biomarker for canine malignancies.
  • Combining TK1 with inflammatory biomarkers like canine C-reactive protein (cCRP) can enhance early tumor detection sensitivity.

Purpose of the Study:

  • To develop and validate a machine learning model, Alertix-Cancer Risk Index (Alertix-CRI), for early canine tumor detection.
  • To integrate canine TK1 protein, cCRP levels, and age into a predictive model.
  • To assess the diagnostic performance of Alertix-CRI compared to individual biomarkers.

Main Methods:

  • Utilized 287 serum samples from healthy dogs and dogs with various tumors.
  • Measured serum TK1 and cCRP levels using ELISA techniques.
  • Developed Alertix-CRI using a generalized boosted regression model (GBM) with 70% training and 30% validation data.

Main Results:

  • Both TK1 and cCRP levels were significantly higher in tumor-bearing dogs (p < 0.0001).
  • TK1 and cCRP showed similar sensitivity (54% vs. 51%) at 95% specificity for overall tumors.
  • Alertix-CRI demonstrated high discriminatory capacity with an AUC of 0.98, achieving 90% sensitivity and 97% specificity.

Conclusions:

  • Alertix-CRI serves as a valuable decision-support tool for clinicians to differentiate malignant diseases in dogs.
  • The model facilitates advancements in precise and dependable diagnostic tools for early cancer detection and therapy monitoring in veterinary medicine.