The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial

The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial - The Utility of Clinical Decision Support from Machine Learning Model for Auscultation: Open-Label Randomized Controlled Pilot Trial

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

JPRN

Registry ID

JPRN-UMIN000048499

Enrollment

Registered

2022-08-01

Start date

2022-07-29

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

cardiopulmonary diseases

Interventions

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

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: We recruit junior resident doctors and general internal medicine doctors from Dokkyo Medical University Hospital.

Exclusion criteria

Exclusion criteria: We exclude the doctors with hearing loss, and the doctors who was unsuitable to participate this study.

Design outcomes

Primary

Measure	Time frame
Total rate of correct answer	—

Secondary

Measure	Time frame
Correct answer rate for each sound Self-confidence in the answer	—

Countries

Japan

Contacts

Public ContactTakanobu Hirosawa

Dokkyo Medical University Department of Diagnostic and Generalist Medicine

hirosawa@dokkyomed.ac.jp0282861111

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026