Breast Cancer
Conditions
Keywords
Breast cancer, Text mining, Big Data, Machine Learning
Brief summary
Primary purpose : To develop a method to automatically extract and structure the information included in numerous medical records from breast cancer patients. Secondary purpose : With this procedure we can analyze the content of ten thousand anonymized textual medical records. This information should enable us to explore many subjects, such as: * The impact of certain therapeutic procedures * The characteristics of sub-groups of patients * Pregnancy associated breast cancers * Risk factors
Interventions
OTHERretrospective medical records analyze
Ten thousand medical records (between years 2000 and 2016) will be analyzed
Sponsors
Quantmetry
University Hospital, Strasbourg, France
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Majority (age \> 18) * Malignant breast tumors * signed informed consent
Exclusion criteria
* Benign breast pathology * Patients not initially treated at the Hôpitaux Universitaires de Strasbourg
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Validate the reliability of a computer-based, automatic information retrieval method specific to medical records from breast cancer multidisciplinary meetings | 6 months |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Breast cancer recurrence rate after some therapeutic procedures | 6 months | Study of the recurrence rate of different subgroups of patients where various procedures were performed |
Countries
France
Contacts
Primary ContactAnne Laudamy
Backup Contactanatta Razafimanantsoa
Outcome results
None listed