Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment

Lung Cancer Clinical Trial

Official title: Development of an Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment Based on Multimodal Data Fusion Using Deep Learning Technology

Status Recruiting

Clinical Trial Summary

To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features, pathological features, and multi-omics information and to develop a multi-modal data fusion-based technology system using artificial intelligence technology based on database.

Clinical Trial Description

The main aims are as follows:

1. To establish a data platform for multi-modal information of common tumors (lung cancer/pulmonary nodules, stomach and colorectal cancers) : electronic medical records (including routine clinical detection, treatment, outcome), pathological image data, medical imaging (CT, MRI, ultrasound, nuclear medicine, etc.), multiple omics data (genome, transcriptome, and metabolome, proteomics) omics data, etiology and carcinogenic exposure information.

2. We will make use of artificial intelligence technology to create the multi-modal medical big data cross-analysis technology and the above disease individualized accurate diagnosis and curative effect prediction models. In order to solve the three key problems of multi-modal data fusion mining, such as unbalanced, small sample size, and poor interpretability, we will establish an artificial intelligence recognition algorithm for image images and pathological images, and use image processing and deep learning technologies to mine multi-level depth visual features of image data and pathological data. In addition, we will use bioinformatics analysis algorithms to conduct molecular network mining and functional analysis of molecular markers at the level of multiple omics technologies (pathologic, genomic, transcriptome, metabolome, proteome, etc.). ;

Related Conditions & MeSH terms

• Artificial Intelligence
• Cancer Risk
• Cancer Screening
• Cancer, Treatment-Related
• Colon Cancer
• Deep Learning
• Lung Cancer
• Lung; Node
• Neoplasms, Second Primary
• Stomach Cancer
• Stomach Neoplasms

• NCT number: NCT05426135
• Study type: Observational
• Source: Wuhan Union Hospital, China
• Contact: Yang Jin
• Phone: 15107177084
• Email: whuhjy@126.com
• Status: Recruiting
• Start date: June 1, 2022
• Completion date: October 2026