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NCT06570486
Contrast Between Traditional Regression Model and AI in Predicting Prolonged Stay Stay After Head and Neck Tumors
trial in Head and Neck Cancer in 700 participants. Currently enrolling.
1 March 2024
Quick facts
| Lead sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University |
|---|---|
| Status | Recruiting now |
| Study type | OBSERVATIONAL |
| Enrollment | 700 |
| Start date | 1 March 2024 |
| Primary completion | 1 March 2024 |
| Estimated completion | 1 April 2025 |
| Sites | 1 location across China |
Conditions studied
- Head and Neck Cancer — all drugs for Head and Neck Cancer →
Sponsor
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Who can join
18 and older, any sex, with Head and Neck Cancer. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
This experiment is an observational study of cohort. By establishing a cohort of patients with head and neck tumors transferred to ICU after surgery, investigators compared the prediction effect of AI and the traditional prediction model on whether patients can be transferred to ICU within 24 hours of head and neck tumors. First retrospective analysis of patients after head and neck tumor surgery, medical records were collected, the test results are divided into training group and validation group according to 7:3, divided into 2 groups according to the patient ICU stay time is greater than 24 hours, the prediction model after the ICU duration of head and neck tumor surgery after more than 24 hours. At the same time, clean the data, train the AI with the data, and compare the effectiveness of both sides with the ROC. After the establishment of prediction model and AI training, the patients included in the cohort were evaluated by prediction model and AI immediately after being transferred to the ICU, predicting the possibility of transferring out of the ICU within 24 hours.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06570486 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Last refreshed: 26 August 2024
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06570486.
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