Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer
NCT ID: NCT04511481
Last Updated: 2020-08-13
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
93 participants
OBSERVATIONAL
2020-04-15
2021-01-01
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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platinum-resistant group
Radiomic Algorithm
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
platinum-sensitive group
Radiomic Algorithm
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
Interventions
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Radiomic Algorithm
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
22 Years
99 Years
FEMALE
No
Sponsors
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Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
OTHER
Responsible Party
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Herui Yao
Principal Investigator
Locations
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Sun Yat-Sen Memorial Hospital of Sun Yat-sen University
Guangzhou, Guangdong, China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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SYSEC-KY-KS-2020-072
Identifier Type: -
Identifier Source: org_study_id
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