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Research on AI Voice Medical Record Generation Algorithm Based on Multimodal Large Models

Research on AI Voice Medical Record Generation Algorithm Based on Multimodal Large Models

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600131919
Enrollment
Unknown
Registered
2026-09-07
Start date
2026-09-30
Completion date
Unknown
Last updated
2026-09-14

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

Conditions

None

Interventions

Patients group (AI speechbased medical note generation modelassisted group):None

Sponsors

Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: Patients 1. Outpatient or inpatient subjects at Ruijin Hospital; 2. Aged between 18 and 75 years old; 3. Clear consciousness with fluent verbal communication, or available family member to conduct verbal consultation on behalf of the subject; 4. Voluntary participation with written informed consent obtained. Clinicians 1. Practicing clinicians at Ruijin Hospital; 2. Working experience = 2 years; 3. Familiar with electronic medical-record documentation standards and proficient in operating computers and medical software; 4. Voluntary participation with written informed consent obtained.

Exclusion criteria

Exclusion criteria: Patients 1. Subjects with language disorder or impaired consciousness who cannot cooperate with audio recording; 2. Subjects with severe mental illness or terminal malignancy who are unable to complete study procedures. Clinicians 1. Novice clinicians without proficiency in electronic medical-record documentation; 2. Clinicians unable to cooperate with system testing and evaluation.

Design outcomes

Primary

MeasureTime frame
Medical record completeness score;Medical record defect incidence rate;Total medical record documentation time;

Secondary

MeasureTime frame
System operational stability;Speech transcription accuracy;Clinician satisfaction score;

Countries

China

Contacts

Public ContactFeiyue Huang

Ruijin Hospital, Shanghai Jiao Tong University School of Medicine

hfy30711@rjh.com.cn+86 15618883818

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Sep 19, 2026