Prospective Real-World Study of Multimodal AI

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ENROLLING_BY_INVITATION

Total Enrollment

2000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-10-01

Study Completion Date

2030-09-30

Brief Summary

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This project proposes to collect prospective multimodal data-such as pathology, imaging, and clinical information-and to perform integrative analyses. AI technologies can offer novel solutions for disease classification, tumor grading, histological subtyping, molecular subtyping, selection of chemotherapy regimens, risk stratification, treatment response prediction, report generation, and intelligent question-answering. This research provides important support for precision medicine and individualized treatment and has significant theoretical and practical implications. Conducting a prospective randomized controlled study better aligns with clinical application requirements and can accelerate the comprehensive deployment of AI systems.

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Detailed Description

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Conditions

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Pancancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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ZSCPH validation dataset

Approximately 1,000 prospective patients across various disease types will have digitized scanned images, imaging information, and clinicopathological data provided, collected from Zhongshan People's Hospital (Zhongshan, Guangdong, China) between October 2025 and September 2030.

No interventions assigned to this group

NFHSMU validation dataset

We conducted a prospective validation study to compare the diagnostic performance among pathologists, our multimodal artificial intelligence model . This study was initiated on October 1, 2025 at Nanfang Hospital, Southern Medical University (NFHSMU).

No interventions assigned to this group

Randomized controlled trial

We conducted a prospective randomized controlled trial to compare the diagnostic performance among pathologists, the multimodal artificial intelligence model, and pathologist-with-model-assisted diagnosis at Nanfang Hospital of Southern Medical University (NFHSMU).The trial commenced data collection on October 1, 2025 to establish the NFHSMU randomized controlled trial dataset. Following quality control, the slides were randomly allocated (1:1:1 ratio) into three groups:Model-only group/Pathologist-only group/Model-assisted pathologist group.

No interventions assigned to this group