Clinical trial · Observational
Multi-Disciplinary Treatment on the Anthropomorphism of Large Language Models
Multi-Disciplinary Treatment on the Anthropomorphism of Large Language Models: A Parallel Controlled Study
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This retrospective clinical trial aims to better explore the potential of large language models in medicine by comparing the effectiveness of MDT consultations conducted by human doctors with those conducted by large language models. The main questions to be addressed are: Does using large language models to conduct anthropomorphic MDT consultations yield better results than using non-anthropomorphic processes? Is there a significant performance gap between MDT consultations conducted by large language models and those conducted by humans? How much greater is the economic benefit of MDT consultations from large language models compared to those conducted by humans? Retrospectively collect MDT consultation records from the past 20 years in northern Sichuan in China, as well as anonymized patient medical records. Group 1: Different large language models are assigned to act as doctors from different departments and as MDT secretaries to summarize consultations. Group 2: The large language model directly outputs diagnostic and treatment recommendations for patients. Compare the outputs of groups 1 and 2 with human performance retrospectively, score them, and select the best model from each department for a re-evaluation through anthropomorphic MDT consultations, once again comparing them to human results.
Conditions
Conditions (6)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cancer | Malignant Neoplasm | ALIAS | 0.90 |
| Disease | — | UNRESOLVED | — |
| Heart Diseases | — | UNRESOLVED | — |
| Infections | — | UNRESOLVED | — |
| Pneumonia | — | UNRESOLVED | — |
| Respiratory Failure | — | UNRESOLVED | — |
Interventions
Interventions (6)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Claude-3.5 Sonnet | Diagnostic Test | — | UNRESOLVED |
| Claude 3 Haiku | Diagnostic Test | — | UNRESOLVED |
| GPT-4o | Diagnostic Test | — | UNRESOLVED |
| GPT-4o mini | Diagnostic Test | — | UNRESOLVED |
| MedicalGPT | Diagnostic Test | — | UNRESOLVED |
| Real Doctors | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (4)
- label
- Anthropomorphized Process Large Language Model Multidisciplinary Treatment Group
- description
- Using a locally deployed MedicalGPT, the commercially available online GPT-4o, Claude-3.5 Sonnet, GPT-4o mini, and Claude 3 Haiku, will each sequentially play the role of physicians from different departments involved in the Multi-Disciplinary Treatment Process. They will then sequentially take on the role of a summarizer to compile their recommendations into a final suggestion or treatment plan.
- interventionNames
- Diagnostic Test: GPT-4o
- Diagnostic Test: GPT-4o mini
- Diagnostic Test: MedicalGPT
- Diagnostic Test: Claude-3.5 Sonnet
- Diagnostic Test: Claude 3 Haiku
- label
- Non-anthropomorphized Process Large Language Model Multidisciplinary Treatment Group
- description
- Using a locally deployed MedicalGPT, the commercial online GPT-4o, Claude-3.5 Sonnet, GPT-4o mini, and Claude 3 Haiku to output multidisciplinary consultation results in a single instance, without separately assuming roles for each department and then compiling the results.
- interventionNames
- Diagnostic Test: GPT-4o
- Diagnostic Test: GPT-4o mini
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * 1\. The medical records include interdisciplinary consultation notes, with recommendations from specialists of various departments and a well-documented final summary. * 2\. The medical records contain data from at least one year prior to and one year following the consultation (including intact reports and imaging records). * 3\. The patient\'s discharge conditions improved due to the multidisciplinary treatment plan after the consultation. Exclusion Criteria: * 1\. The medical records do not include multidisciplinary consultation notes, or the recommendations from various departmental physicians and the final summary notes are incomplete or inadequate. * 2\. The medical records lack data from 1 year before and after the consultation, or miss necessary reports and imaging data, resulting in incomplete documentation. * 3\. The patient\'s condition at discharge has not improved following the multidisciplinary treatment plan, or the condition has worsened.
References
Publications (1)
- RESULTSchroder C, Medves J, Paterson M, Byrnes V, Chapman C, O'Riordan A, Pichora D, Kelly C. Development and pilot testing of the collaborative practice assessment tool. J Interprof Care. 2011 May;25(3):189-95. doi: 10.3109/13561820.2010.532620. Epub 2010 Dec 23. PMID 21182434