malignant tumor
Conditions
Interventions
observation group:use the optimal feature set and training methods for deep learning prediction of field gamma passing rates
control group:use the non-optimal feature set and training methods for deep learning prediction of field gamma passing rates
Sponsors
Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine
Eligibility
Sex/Gender
All
Age
18 Years to 90 Years
Inclusion criteria
Inclusion criteria: 1. Patients with malignant tumor and have received radiotherapy in our hospital; 2. Patients with ages ranging from 18 to 90 regardless of gender; 3. Patients were positioned in the supine or prone position with the hands at the sides of the body or raised; 4. The patient's CT scan covered the irradiated area and extended 10 cm up and down, with a layer thickness less than 5 mm; 5. Informed consent and volunteer patients. The process of obtaining the informed consent shall comply with the GCP regulations.
Exclusion criteria
Exclusion criteria: 1. Patients who are pregnant and lactating women; 2. Patients who are unable to give full informed consent due to intellectual or behavioral disorders.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| mean absolute error of gamma passing rates prediction; | — |
Secondary
| Measure | Time frame |
|---|---|
| accuracy of gamma passing rates classification ; | — |
Countries
China
Contacts
Public ContactSong Wei
Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine
Outcome results
None listed