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A new strategy for constructing a neural network model based on a large sample of multi-modal data to optimize the efficacy evaluation of solid tumors

A new strategy for constructing a neural network model based on a large sample of multi-modal data to optimize the efficacy evaluation of solid tumors

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000038481
Enrollment
Unknown
Registered
2020-09-23
Start date
2021-01-01
Completion date
Unknown
Last updated
2021-01-05

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

Conditions

Primary Liver Cancer

Interventions

case series:not applicable

Sponsors

Zhongshan Hospital Affiliated to Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients aged 18-80 years, male or female; 2. Pathological diagnosis: hepatocellular carcinoma, intrahepatic cholangiocarcinoma or mixed hepatocellular cholangiocarcinoma; 3. For patients with complete follow-up data, the specimens were well preserved without damage; 4. Patients who meet at least one of the following treatment schemes (surgical resection of primary liver cancer, combined with neoadjuvant chemotherapy or adjuvant chemotherapy (immune / targeted + immune / targeted) or interventional therapy; 5. Chemotherapy (immuno / targeting + immuno / targeting) should be used for those patients with advanced primary liver cancer who have not been surgically resected.

Exclusion criteria

Exclusion criteria: Patients with severe heart, brain, lung, kidney and blood system diseases, allografts.

Design outcomes

Primary

MeasureTime frame
response;—

Countries

China

Contacts

Public ContactYi Yong

Zhongshan Hospital Affiliated to Fudan University

yi.yong@zs-hospital.sh.cn+86 15821328520

Outcome results

None listed

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