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Name:
UMIN ID:

Recruitment status No longer recruiting
Unique ID issued by UMIN UMIN000036839
Receipt No. 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

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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
Email 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
Email dyokokawa6@chiba-u.jp

Sponsor
Institute Chiba University
Institute
Department

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
Email 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
URL(English) https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041969

Research Plan
Registered date File name

Research case data specifications
Registered date File name

Research case data
Registered date File name


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