Application of the AI Platform iLN Based on DeepSeek in the Teaching of Lupus Nephritis

NCT07706998 | Not Yet Recruiting

• 1 other identifier: NDY2025004
• Study Type: interventional
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

Aim: To evaluate the application effect of the teaching platform iLN in the teaching of lupus nephritis, aiming to provide practical experience and evidence-based support for the implementation of generative AI technology in professional medical education. Method: Based on the DeepSeek large language model, the investigators developed "iLN" - an interactive teaching platform for lupus nephritis. This platform integrates the latest authoritative textbooks, clinical guidelines, pathological atlases, and real clinical cases, and includes seven core modules, such as "case interaction", "knowledge teaching", and "AI question answering". The investigators conducted a randomized controlled trial (RCT) on 50 fourth-year undergraduate students from Nanjing University School of Medicine to evaluate the effectiveness of the iLN platform compared to traditional teaching methods. The teaching effect was evaluated through objective test scores and questionnaires about student satisfaction and platform usability.

Conditions

Learning

Keywords

Generative artificial intelligence; DeepSeek; Lupus nephritis; Medical education

Outcome Measures

Primary Outcomes (1)

• Objective Test Scores

  Unified in-class objective test (20 multiple-choice questions, 5 points each, 100 points total)，the higher the score, the better the performance.

  On the day of the end of the teaching session within 30 minutes after teaching session

Secondary Outcomes (1)

• Questionnaire Survey

  On the day of the end of the teaching session within 60 minutes after teaching session.

Study Arms (2)

GAI-assisted teaching group

EXPERIMENTAL

GAI-assisted teaching group: Students used various platform modules for self-directed learning under the instructor's guidance: (1) In the "Case Interaction" module, students interacted with three virtual cases by inputting natural language questions (e.g., "Does the patient have edema?", "What is the patient's proteinuria level?", "What are the light microscopy results of the renal biopsy?"). The platform automatically determines the question type and provides the corresponding information, while the visualized patient model on the right side simultaneously highlights the affected systems already identified, and the case information acquisition progress bar is updated dynamically; (2) When students encounter difficulties, they can invoke DeepSeek in real time for immediate answers through the "AI Q\&A" module; (3) After completing case interactions, students proactively summarized the history characteristics, with the instructor providing supplementary input; (4) The instructor guided

Device: An iLN interactive teaching platform

Traditional teaching group

OTHER

Traditional teaching group: Adopted the traditional PowerPoint (PPT) lecture mode. The instructor used uniformly prepared PPT courseware to sequentially lecture on the SLE overview, LN clinical manifestations, laboratory tests, pathological classification, diagnostic criteria, treatment plans, and prognosis evaluation. The courseware included static pathological and clinical manifestation images.

Other: PPT

Interventions

An iLN interactive teaching platform DEVICE

An iLN interactive teaching platform for lupus nephritis based on the DeepSeek large language model and by integrating the latest authoritative textbooks, guidelines, and clinical pathology materials.

GAI-assisted teaching group

PPT OTHER

Adopted the traditional PowerPoint (PPT) lecture mode. The instructor used uniformly prepared PPT courseware to sequentially lecture on the SLE overview, LN clinical manifestations, laboratory tests, pathological classification, diagnostic criteria, treatment plans, and prognosis evaluation. The courseware included static pathological and clinical manifestation images.

Traditional teaching group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• As a student majoring in clinical medicine
• Volunteering to participate in the study

You may not qualify if:

• Inability to understand, read, or communicate in Chinese
• Failure to participate in any stage of the study (e.g. in-class education session, or post-test)
• Requesting withdrawal from the study

Sponsors & Collaborators

• Nanjing University: lead

Study Sites (1)

Nanjing university

Nanjing, Jiangsu, 210016, China

Location

Related Publications (1)

• Lin Y, Luo Z, Ye Z, Zhong N, Zhao L, Zhang L, Li X, Chen Z, Chen Y. Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review. JMIR Med Educ. 2025 Oct 23;11:e71125. doi: 10.2196/71125.

  PMID: 41128430 BACKGROUND

MeSH Terms

Conditions

Lupus Nephritis

Condition Hierarchy (Ancestors)

Glomerulonephritis; Nephritis; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Lupus Erythematosus, Systemic; Connective Tissue Diseases; Skin and Connective Tissue Diseases; Autoimmune Diseases; Immune System Diseases

Central Study Contacts

Hao Bao, Doctor.

CONTACT

86-15062213937; bhao@nju.edu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: June 30, 2026
• First Posted: July 16, 2026
• Study Start: July 1, 2026
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: July 16, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)