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

You might also read

Related Articles

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

Sort by
Same author

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records.

Cancers·2023
Same author

CASIDE: A data model for interoperable cancer survivorship information based on FHIR.

Journal of biomedical informatics·2021
Same author

PattRec: An easy-to-use CNV detection tool optimized for targeted NGS assays with diagnostic purposes.

Genomics·2019
Same author

Free-access copy-number variant detection tools for targeted next-generation sequencing data.

Mutation research. Reviews in mutation research·2019
Same author

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.

BioMed research international·2017
Same author

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

Journal of medical systems·2017
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: Sep 20, 2025

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications
14:14

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Published on: February 28, 2014

16.0K

Interoperable Medical Application for CTC Counting.

Victoria M Cal-González1, Lorena González-Castro1,2

  • 1Department of eHealth, Galician Research & Development Center in Advanced Telecommunications, Vigo, Spain.

Studies in Health Technology and Informatics
|June 8, 2022
PubMed
Summary
This summary is machine-generated.

This study details an AI application for counting Circulating Tumor Cells (CTCs) to aid in early cancer metastasis and recurrence detection. The focus is on selecting key data and ensuring compliance with international standards for improved diagnostics.

Keywords:
CirculatingClinicalDecision Support SystemsHealth Information InteroperabilityNeoplastic Cells

More Related Videos

Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells
05:58

Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells

Published on: October 13, 2023

1.4K
Rapid Isolation of Viable Circulating Tumor Cells from Patient Blood Samples
07:32

Rapid Isolation of Viable Circulating Tumor Cells from Patient Blood Samples

Published on: June 15, 2012

26.9K

Related Experiment Videos

Last Updated: Sep 20, 2025

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications
14:14

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Published on: February 28, 2014

16.0K
Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells
05:58

Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells

Published on: October 13, 2023

1.4K
Rapid Isolation of Viable Circulating Tumor Cells from Patient Blood Samples
07:32

Rapid Isolation of Viable Circulating Tumor Cells from Patient Blood Samples

Published on: June 15, 2012

26.9K

Area of Science:

  • Computational biology
  • Medical informatics
  • Oncology

Background:

  • Circulating Tumor Cells (CTCs) are crucial biomarkers for cancer metastasis and recurrence.
  • Standardized data handling is essential for reliable CTC analysis and clinical application.
  • Current methods for CTC analysis may lack interoperability and standardized data structures.

Purpose of the Study:

  • To describe the development of an interoperable AI-powered application for Circulating Tumor Cells (CTCs) counting.
  • To identify critical information for the early detection of distant metastasis and local recurrence using CTCs.
  • To define a data structure compliant with international standards and ontologies for CTC data.

Main Methods:

  • Development of an AI-powered application for automated CTC counting.
  • Selection of key data features indicative of metastasis and recurrence.
  • Definition of a data structure adhering to established international standards and ontologies.

Main Results:

  • An AI application for CTC counting has been developed.
  • Key data elements for early detection of metastasis and recurrence have been identified.
  • A standardized data structure compliant with international standards and ontologies has been defined.

Conclusions:

  • The developed AI application facilitates interoperable CTC counting.
  • Standardized data structures enhance the reliability of CTC analysis for early cancer detection.
  • This approach supports improved clinical decision-making in oncology through advanced biomarker analysis.