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Name
UMIN ID

Recruitment status Preinitiation
Unique ID issued by UMIN UMIN000048499
Receipt No. R000055270
Scientific Title The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial
Date of disclosure of the study information 2022/08/01
Last modified on 2022/07/28

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Basic information
Public title The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial
Acronym The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial
Scientific Title The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial
Scientific Title:Acronym The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial
Region
Japan

Condition
Condition cardiopulmonary diseases
Classification by specialty
Medicine in general Cardiology Pneumology
Classification by malignancy Others
Genomic information NO

Objectives
Narrative objectives1 We developed the clinical decision support system of machine learning model to assist cardiopulmonary auscultation. We hypothesized the system improve the correct answer rate of auscultation.
Basic objectives2 Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase

Assessment
Primary outcomes Total rate of correct answer
Key secondary outcomes Correct answer rate for each sound
Self-confidence in the answer

Base
Study type Interventional

Study design
Basic design Parallel
Randomization Randomized
Randomization unit Individual
Blinding Open -no one is blinded
Control Active
Stratification NO
Dynamic allocation NO
Institution consideration
Blocking
Concealment

Intervention
No. of arms 2
Purpose of intervention Diagnosis
Type of intervention
Device,equipment
Interventions/Control_1 The participant of intervention group auscultate the previous recorded sounds with clinical decision support system from machine learning model. They completed the types of sounds they recognized and the self-confidence in a structured questionnaire.
Interventions/Control_2 The participant of control group auscultate the previous recorded sounds. They completed the types of sounds they recognized and the self-confidence in a structured questionnaire.
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 We recruit junior resident doctors and general internal medicine doctors from Dokkyo Medical University Hospital.
Key exclusion criteria We exclude the doctors with hearing loss, and the doctors who was unsuitable to participate this study.
Target sample size 24

Research contact person
Name of lead principal investigator
1st name Takanobu
Middle name
Last name Hirosawa
Organization Dokkyo Medical University
Division name Department of Diagnostic and Generalist Medicine
Zip code 321-0293
Address 880 Kitakobayashi, Mibu-cho, Shimotsuga-gun, Tochigi
TEL 0282861111
Email hirosawa@dokkyomed.ac.jp

Public contact
Name of contact person
1st name Takanobu
Middle name
Last name Hirosawa
Organization Dokkyo Medical University
Division name Department of Diagnostic and Generalist Medicine
Zip code 321-0293
Address 880 Kitakobayashi, Mibu-cho, Shimotsuga-gun, Tochigi
TEL 0282861111
Homepage URL
Email hirosawa@dokkyomed.ac.jp

Sponsor
Institute Dokkyo Medical University
Institute
Department

Funding Source
Organization Dokkyo Medical University
Organization
Division
Category of Funding Organization Self funding
Nationality of Funding Organization

Other related organizations
Co-sponsor
Name of secondary funder(s)

IRB Contact (For public release)
Organization The Ethics Committee of Dokkyo Medical University
Address 880 Kitakobayashi, Mibu-cho, Shimotsuga-gun, Tochigi
Tel 0282861111
Email r-kenkyu@dokkyomed.ac.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
2022 Year 08 Month 01 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
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 Preinitiation
Date of protocol fixation
2022 Year 07 Month 25 Day
Date of IRB
Anticipated trial start date
2022 Year 07 Month 29 Day
Last follow-up date
2024 Year 12 Month 31 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other
Other related information

Management information
Registered date
2022 Year 07 Month 28 Day
Last modified on
2022 Year 07 Month 28 Day


Link to view the page
URL(English) https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000055270

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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