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AI-assisted education enhances diagnostic accuracy and surgical planning for pulmonary nodules in thoracic surgery residents: a randomized crossover trial

AI-assisted education enhances diagnostic accuracy and surgical planning for pulmonary nodules in thoracic surgery residents: a randomized crossover trial

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ChiCTR
Registry ID
ChiCTR2500114903
Enrollment
Unknown
Registered
2025-12-18
Start date
2025-12-18
Completion date
Unknown
Last updated
2026-01-05

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

Conditions

Lung cancer

Interventions

A:First, AI-assisted teaching, followed by a 6-week washout period before crossover to conventional teaching.
B:Start with conventional teaching, then cross over to AI-assisted teaching after a 6-week washout period.

Sponsors

The Second Xiangya Hospital, Central South University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age >=18 years, no restriction on sex; 2. In-training medical students or resident physicians who have signed informed consent; 3. Possess basic competency in chest CT interpretation (e.g., completion of departmental CT reading training or assessment).

Exclusion criteria

Exclusion criteria: 1. Individuals unable to complete both stages of evaluation or those scheduled for rotation/leave; 2. Individuals with prior extensive involvement in similar AI projects or those with memorized exposure to the same teaching case set; 3. Refusal to participate in the study.

Design outcomes

Primary

MeasureTime frame
Clinical decision making;

Secondary

MeasureTime frame
Self-confidence;Time per case;

Countries

China

Contacts

Public ContactXue He

The Second Xiangya Hospital, Central South University

hexuehuxi@csu.edu.cn+86 731 8529 5188

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026