UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000036839 |
|---|---|
| Receipt number | R000041969 |
| Scientific Title | Development of diagnostic engine using natural language extracted from medical records |
| Date of disclosure of the study information | 2021/03/31 |
| Last modified on | 2019/05/24 11:55:36 |
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Basic information
Public title
Development of diagnostic engine using natural language extracted from medical records
Acronym
Development of diagnostic engine using natural language extracted from medical records
Scientific Title
Development of diagnostic engine using natural language extracted from medical records
Scientific Title:Acronym
Development of diagnostic engine using natural language extracted from medical records
Region
| Japan |
Condition
Condition
General Medicine
Classification by specialty
| Medicine in general |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
Construction of structured database and invention of diagnostic engine
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
F Measure
Key secondary outcomes
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 20 | years-old | <= |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
First visit patient to general medicine department
Key exclusion criteria
Person who did not get consent
Target sample size
20000
Research contact person
Name of lead principal investigator
| 1st name | Daiki |
| Middle name | |
| Last name | Yokokawa |
Organization
Chiba University Hospital
Division name
Department of General Medicine
Zip code
260-8677
Address
Chiba city
TEL
0432227171
dyokokawa6@chiba-u.jp
Public contact
Name of contact person
| 1st name | Daiki |
| Middle name | |
| Last name | Yokokawa |
Organization
Chiba University Hospital
Division name
Department of General Medicine
Zip code
260-8677
Address
1-8-1, Inohana, Chuo-ku, Chiba city
TEL
0432227171
Homepage URL
dyokokawa6@chiba-u.jp
Sponsor or person
Institute
Chiba University
Institute
Department
Personal name
Funding Source
Organization
Ricoh IT Solutions Co.,Ltd.
Organization
Division
Category of Funding Organization
Profit organization
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Chiba University Hospital
Address
1-8-1, Inohana, Chuo-ku, Chiba city
Tel
043-222-7171
dyokokawa6@chiba-u.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
Other administrative information
Date of disclosure of the study information
| 2021 | Year | 03 | Month | 31 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
20000
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
No longer recruiting
Date of protocol fixation
| 2019 | Year | 01 | Month | 04 | Day |
Date of IRB
| 2019 | Year | 01 | Month | 04 | Day |
Anticipated trial start date
| 2019 | Year | 01 | Month | 31 | Day |
Last follow-up date
| 2019 | Year | 01 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
After approval of the ethics review board, the medical records of the study subject meeting the selection criteria are taken out from the database. In the extraction, all items corresponding to personal information are deleted and anonymized.
The text data of the anonymized medical record is subjected to morphological analysis by a computer held in the medical department to extract data (Key data) considered to be necessary for diagnostic reasoning. Design a program that uses python to determine which information (Value data) the extracted information is "yes / no", and stores the clinical diagnostic name-Key data-Value data in one database.
This data is used to design and develop a diagnostic engine. Models that can be considered Bayesian networks, decision trees, or models using deep learning (especially, regression neural networks). These models are used to match the clinical diagnostic name finally determined by the doctor, or to measure its accuracy, to improve the engine.
Management information
Registered date
| 2019 | Year | 05 | Month | 24 | Day |
Last modified on
| 2019 | Year | 05 | Month | 24 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041969
