Summary
Description:
A highly curated, multi-modal Gastric Cancer dataset to develop a deep learning algorithm capable of predicting the MSS/MSI phenotype in Gastric Cancer from histology slides.
Access Tier:
Controlled
Contact Point:
Health Theme:
Cancer
Health Category:
Electronic Health Records (EHRs)
Number of Unique Individuals:
130
Documentation
Documentation:
A highly curated, multi-modal Gastric Cancer dataset to develop a deep learning algorithm capable of predicting the MSS/MSI phenotype in Gastric Cancer from histology slides.
Coverage
Spatial
Spatial Coverage:
West Midlands
Temporal
Start Date:
01 January 2012
Frequency:
STATIC
Date of First Release:
19 February 2025
Provenance
Origin
Purpose:
Study
Collection Situation:
- Clinic
- Secondary care - In-patients
- Secondary care - Outpatients
- Services
Image Contrast:
Not stated
Method of Collection:
EPR, LIMS
Access and Governance
Access
Access Rights:
Information Governance and Ethics - West Midlands Secure Data Environment (https://westmidlandssde.nhs.uk/information-governance-and-ethics)
Delivery Lead Time:
2-6 months
Health Data Access Body:
This publication uses data from WMSDE, an ethically approved NHS Secure Data
Environment (NRES Reference 24/YH/0022)
Format and Standards
Language:
English
Format:
SQL
Conforms To:
OTHER
Coding System:
ICD10
Data Distribution
Data Status:
Not available
Distribution:
Data Request Process - West Midlands Secure Data Environment
(https://westmidlandssde.nhs.uk/research/data-request), Please email
wmsde@uhb.nhs.uk
Observations
Name
Population Type
Value
Description
Variable Measured
Unit Code
Observation Date
Number of Records
Minimum Typical Age
Maximum Typical Age
Persons
130
130 multimodal patients.
Count
20 February 2025
130
0
0
Origin
Name:
Data Catalogue