Clinical trial · Observational
Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck Patients
Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck
NCT05607225CI-TRIAL-00061995unknownClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
to develop a deep learning-based model to grade the severity of radiation dermatitis (RD) and predict the severity of radiation dermatitis in patients with head and neck cancer undergoing radiotherapy, so as to provide support for doctors' diagnosis and prediction.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Head and Neck Cancer | Malignant Head and Neck Neoplasm | ALIAS | 0.90 |
| Radiation Dermatitis | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (5)
- measure
- Accuracy
- timeFrame
- July 1, 2022 to June 30, 2025
- description
- Evaluate the rate of deep learning based rating model in accordance with experts' assessment.
- measure
- Precision
- timeFrame
- July 1, 2022 to June 30, 2025
- description
- The proportion of positive samples in the positive prediction result
- measure
- Recall
- timeFrame
- July 1, 2022 to June 30, 2025
- description
- The proportion of positive samples that were predicted to be positive
- measure
- F1-measure
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Age ≥ 18 years old. * Histologically or cytologically confirmed head and neck carcinoma confirmed by pathology. * Receive radical radiotherapy including neck area * Informed consent. Exclusion Criteria: * unable to cooperate with image acquisition
References
Publications (0)
Data not yet available
No reference posted for this study.