Clinical trial · Observational
D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology
D-Lung: An Analytics Platform for Primary Lung Cancer Screening, Diagnosis and Management Based on Deep Learning Technology
- 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)
Lung cancer is one of main cause of cancer death in worldwide, characterized of low 5-year survival rate of less than 20%. Pulmonary nodule is considered as the typical imaging manifestation in early stage of lung cancer. The National Lung Screen Trial has demonstrated that the mortality rates could decline greatly, by the utility of low-dose helical computed tomography for screen of pulmonary nodules. Thus, automatic detection, diagnosis and management of pulmonary nodules, play the vital roles in computer-aided lung cancer screening and early intervention.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| computed tomography | Radiation | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (4)
- measure
- accuracy
- timeFrame
- 2 years
- description
- proportion of true results(both true positives and true negatives) among whole instances
- measure
- sensitivity
- timeFrame
- 2 years
- description
- true positive rate in percentage(%) derived by ROC analysis
- measure
- specificity
- timeFrame
- 2 years
- description
- true negative rate in percentage (%) derived by ROC analysis
- measure
- area under curve (AUC)
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Subjects with suspicious lung nodules. * Thin-layer thoracic CT and pathology examination have been performed for suspicious lung nodules. Exclusion Criteria: * Subjects with accompanied lesions on CT images that may interfere to lung nodules analysis
References
Publications (0)
Data not yet available