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A Prediction Model and Assisted Decision-making System of Fertilization Disorders

NCT05730764 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 260

Last updated 2023-11-22

No results posted yet for this study

Summary

The goal of this clinical trial is to test the accuracy of the forecasting system we develop. The main question it aims to answer is:

* Whether the clinical prediction system predicts the incidence of fertilization disorders accurately.
* The fertilization disorder prediction system predicts whether and how much the outcome differs from the doctor.

Participants will receive treatment assisted by a predictive system or receive general treatment.

Researchers will compare incidence of fertilization disorders to see if the fertilization disorder prediction system makes correct predictions.

Conditions

Interventions

DIAGNOSTIC_TEST

Accurate prediction of fertilization disorders and clinical decision support systems assist doctors in decision-making

With the assistance of accurate prediction of fertilization disorders and clinical decision support systems, clinicians predict and judge the probability and key factors of fertilization disorders of patients, and formulate and implement personalized diagnosis and treatment plans based on the prediction results

DIAGNOSTIC_TEST

Clinicians follow a routine protocol

Treatment is performed by the clinician according to the usual protocol.

Sponsors & Collaborators

  • Peking University Third Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
45 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-15
Primary Completion
2024-08-01
Completion
2024-08-01

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05730764 on ClinicalTrials.gov