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AI tool forecasts stomach cancer recurrence with high accuracy

NCT ID NCT07243847

Knowledge-focused Sponsor: Fudan University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This completed study from Fudan University used a deep learning model to predict whether stomach cancer will come back after surgery. Researchers analyzed data from 5,000 patients across multiple hospitals in Eastern Asia. The model showed strong ability to identify early recurrence and could help doctors tailor treatment plans, including for those receiving chemotherapy before or after surgery.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
deep learning model
What this could lead to
If successful, this model could help doctors predict which gastric cancer patients are at higher risk of recurrence, enabling more personalized follow-up and treatment decisions.
What could go wrong
This is a completed observational study, not a treatment trial. The model's predictions need further validation in real-world settings before routine use.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

5,000 people

The number who actually took part.

Started

Jan 2000

Finished

Nov 2025

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

A retrospective analysis was conducted on the clinicopathological data of patients who underwent radical gastrectomy for gastric cancer between 2001 and 2022 at 13 tertiary hospitals in China.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: Pathologically confirmed gastric adenocarcinoma; No distant metastases confirmed by preoperative examinations such as chest X-ray, abdominal ultrasonography, and upper abdominal computed tomography; Achievement of R0 resection. Exclusion Criteria: Presence of distant metastases detected preoperatively or intraoperatively; Prior neoadjuvant chemotherapy or radiotherapy; Incomplete general clinical data.

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Conditions

The condition(s) this trial relates to.

gastric adenocarcinoma gastric cancer gastric neoplasm

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Gastric cancer (GC)

More trials for these conditions

Other studies related to the condition(s) this trial covers.