ArticleJournal of cancer research and clinical oncology2026
AI-MDT: an automatic and intelligent multidisciplinary team consultations platform for lung cancer diagnosis.
Article in Journal of cancer research and clinical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- [Current Status of Multidisciplinary Team Consultation for Lung Cancer and Prospects under the Empowerment of Medical Large Models].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026Review
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeMultidisciplinary team (MDT) consultations are crucial for managing pulmonary nodules, yet face challenges in efficiency, evidence-based decision support, and data utilization within the MDT process. We present an integrated artificial intelligence (AI)-MDT platform that serves as an assistive tool for lung cancer MDT workflows by incorporating AI across various processes.The aim of this study is to evaluate the clinical utility and preliminary efficacy of the AI-MDT platform.
methodsThe platform comprises three core modules: process automation, intelligent decision support, and diagnostic assistance. It integrates a real-time, evidence-based knowledge base powered by large language models and deep learning, with computer vision for automatic lesion detection and feature analysis. A web-based interface allows users to interact seamlessly with the AI-MDT platform.
resultsSince its implementation in November 2023 at a tertiary Grade A hospital in China, the platform has been involved in 879 consultations, including 811 patients. AI-generated diagnostic recommendations were utilized 852 times, and decision-making support was used in 744 cases. The platform significantly increased consultation volume, reduced expert time, and enhanced data utilization compared to traditional MDT.
conclusionsIt offers clinicians tools to improve diagnostic quality and work efficiency, highlighting its significant clinical application value. These findings suggest that the proposed platform contributes to the emerging research on advances precision lung cancer management by integrating a continually updated evidence base and intelligent imaging methodologies, having potential implications for MDT processes across various medical specialties.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.