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Construction of Early Warning Model for Pulmonary Complications Risk of Surgical Patients Based on Multimodal Data Fusion

NCT06057688 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1770

Last updated 2023-09-28

No results posted yet for this study

Summary

The goal of this observational study is to establish an intelligent early warning system for acute and critical complications of the respiratory system such as pulmonary embolism and respiratory failure. Based on the electronic case database of the biomedical big data research center and the clinical real-world vital signs big data collected by wearable devices, the hybrid model architecture with multi-channel gated circulation unit neural network and deep neural network as the core is adopted, Mining the time series trends of multiple vital signs and their linkage change characteristics, integrating the structural nursing observation, laboratory examination and other multimodal clinical information to establish a prediction model, so as to improve patient safety, and lay the foundation for the later establishment of a higher-level and more comprehensive artificial intelligence clinical nursing decision support system.

Issues addressed in this study

1. The big data of vital signs of patients collected in real-time by wearable devices were used to explore the internal relationship between the change trend of vital signs and postoperative complications (mainly including infection complications, respiratory failure, pulmonary embolism, cardiac arrest). Supplemented with necessary nursing observation, laboratory examination and other information, and use machine learning technology to build a prediction model of postoperative complications.
2. Develop the prediction model into software to provide auxiliary decision support for clinical medical staff, and lay the foundation for the later establishment of a higher-level and more comprehensive AI clinical decision support system.

Conditions

Sponsors & Collaborators

  • Renrong Gong

    lead OTHER

Principal Investigators

  • GONG professor · West China Hospital

Eligibility

Min Age
14 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-08-01
Primary Completion
2024-10-01
Completion
2024-12-31

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 NCT06057688 on ClinicalTrials.gov