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Research on an automatic T-stage model for nasopharyngeal carcinoma MRI imaging based on deep learning

Research on an automatic T-stage model for nasopharyngeal carcinoma MRI imaging based on deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400080515
Enrollment
Unknown
Registered
2024-01-31
Start date
2024-02-01
Completion date
Unknown
Last updated
2024-02-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Nasopharyngeal carcinoma

Interventions

Training set:None
Verification set:None

Sponsors

Central Hospital of Guangdong Nongken
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: 1. Nasopharyngeal cancer patients diagnosed by tissue or cellular pathology;2. Without undergoing anti-tumor treatments such as radiotherapy, chemotherapy, immunology, and targeted therapy;3. Age range from 18 to 85 years old;

Exclusion criteria

Exclusion criteria: 1. Through anti-tumor treatments such as radiotherapy, chemotherapy, immunology, and targeted therapy;2. Merge with other tumors;3. Incomplete clinical data;;

Design outcomes

Primary

MeasureTime frame
susceptibility;Specificity;—

Secondary

MeasureTime frame
Accuracy;—

Countries

China

Contacts

Public ContactDili Song

Central Hospital of Guangdong Nongken

719055085@qq.com+86 187 1818 9223

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026