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RecruitingNCT06534814Updated Aug 2, 2024

Development and Application of an Artificial Intelligence-driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis

An observational study in The Primary Focus of This Study is on Gastric Cancer, sponsored by Hebei Medical University. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-08-02.

Sponsored by Hebei Medical University · Observational

From the registry’s dates

  • Primary completion was expected by Dec 2025, 10 months ago, but the record still lists the study as recruiting.
  • Started Jul 2024; still recruiting 2 years 4 months later.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
300
Ages
18 Years and older
Sex
All
01

Where this study stands

Counted across the records on this site · 2026-11-12

Among 15 studies in Stomach Neoplasms by Hebei Medical University — 4 open to participants now, 5 under way, none of them phase 3. Stomach Neoplasms · Hebei Medical University.

Started
2024
with 1 other
Observational
Only one
of the 15
Registered
13th of 15
by date

Among the 15 studies in Stomach Neoplasms by Hebei Medical University, this one is one of 2 that started in 2024, is the only observational one, and was the 13th registered.

By phase

15 studies; the count open now beside each. This study's row is marked.

Phase 25 · 1 open
No phase4 · 2 open
Phase 2/33 · 0 open
Phase 42 · 0 open
Observationalthis study1 · 1 open

By the year they started

First in 2012; this study’s year is marked. 2 started in 2024.

Size and results

Median enrollment 48 across the 14 interventional studies, 300 across the 1 observational. Of the 1 that completed or were terminated, 0 (0%) have results posted.

Watch this landscapeDownload CSVWith an account: a weekly mail of what changed among 15 studies in Stomach Neoplasms by Hebei Medical University, or all of them as a file.
02

Study summary

The clinical trial titled "Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis" aims to enhance the detection and treatment of gastric cancer through the utilization of cutting-edge artificial intelligence (AI) technology. This study will develop an AI-driven model designed to accurately identify lymph node metastasis in patients with gastric cancer, which is crucial for staging the disease and planning effective treatment strategies.

The trial will involve a multidisciplinary team of oncologists, radiologists, data scientists, and AI experts who will collaborate to create a robust and precise identification system. Participants will undergo standard diagnostic procedures, and the AI model will analyze imaging and pathological data to predict lymph node involvement.

By comparing the AI model's predictions with traditional diagnostic methods, the study seeks to validate the model's accuracy and efficiency. This approach is expected to improve early detection rates, reduce diagnostic errors, and ultimately lead to better clinical outcomes for patients with gastric cancer. The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments.

03

Conditions studied

  • The Primary Focus of This Study is on Gastric Cancer

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04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Sampling method
Non-probability sample

Study population

The study population for the clinical trial titled "Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis (AID-GLNM)" will consist of patients diagnosed with gastric cancer, with a focus on those exhibiting lymph node involvement.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  1. Diagnosis of Gastric Cancer: Confirmed diagnosis of gastric cancer, either newly diagnosed or recurrent.
  2. Lymph Node Involvement: Suspected or confirmed involvement of lymph nodes, as indicated by imaging studies or pathology reports.
  3. Age: Patients aged 18 years or older.
  4. Performance Status: An (ECOG) performance status of 0 to 2, indicating a functional status that allows participation in the study.
  5. : Ability to provide written informed consent to participate in the study.

Exclusion criteria

Exclusion Criteria:

  1. Pregnancy or Lactation: Pregnant or lactating women, due to potential risks to the fetus or infant.
  2. Severe Comorbid Conditions: Presence of severe comorbid medical conditions that could interfere with the study or pose additional risks.
  3. Previous AI-Driven Diagnostic Intervention: Prior use of any AI-driven diagnostic models specifically for gastric cancer lymph node .
  4. Inability to Comply: Inability or unwillingness to comply with study procedures, including follow-up visits and data collection.
  5. Mental or Cognitive Impairment: Conditions that impair the ability to provide or participate effectively in the study.
Terms in these criteria, in plain language(3)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

ECOG performance status

A scale of how much an illness limits everyday activity. For people being assessed to join a study, scores run from 0 (fully active) to 4; lower is more active.

0
Fully active, no restrictions.
1
Limited in strenuous activity, but walking and able to do light work, such as housework or office work.
2
Walking and able to look after yourself, but unable to work; up and about more than half of waking hours.
3
Able to look after yourself only in part; in bed or a chair more than half of waking hours.
4
Unable to look after yourself at all; in bed or a chair all day.

Studies most often ask for 0–1 or 0–2. Your doctor gives the score; the WHO scale uses the same steps. The full scale also has 5, which records death.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

Metastases

Cancer that has spread from where it began to other parts of the body. “Metastatic” cancer is cancer that has spread this way.

05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
300 participants (estimated)
Patient registry
No

Interventions

  • Diagnostic testAI-Driven Identification Model for Gastric Cancer Lymph Node Metastasis (AID-GLNM)

    The AI-Driven Identification Model for Gastric Cancer Lymph Node Metastasis (AID-GLNM) intervention involves the development and application of an advanced artificial intelligence (AI) system specifically designed to enhance the identification and characterization of lymph node metastasis in patients diagnosed with gastric cancer.

06

What researchers measure

Primary outcomes

  1. Identification of metastatic lymph nodes

    A prediction model based on artificial intelligence technology was constructed to accurately identify metastatic perigastric lymph nodes before surgery.

    Time frame: 2025-12-31

07

Study locations

1 of 1 sites recruiting
08

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Aug 2, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
09

Registry details

Key details

Study ID
NCT06534814
Lead sponsor
Hebei Medical University
Responsible party
Qun Zhao (Professor, Hebei Medical University) — Principal investigator
First posted
Aug 2, 2024
Start date
Jul 1, 2024
Primary completion
Dec 31, 2025 (estimated)
Completion
Jul 30, 2030 (estimated)
Last update
Aug 2, 2024

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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No contact was published for this record. The registry link below has the sponsor’s details.

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Discussion

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