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NCT05426135 | RECRUITING | Artificial Intelligence


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

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Information provided by (Responsible Party):

Yang Jin

Brief 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.

Condition or disease

Artificial Intelligence

Deep Learning

Lung Cancer

Lung; Node

Stomach Cancer

Colon Cancer

Cancer Risk

Cancer Screening

Cancer, Treatment-Related

Detailed 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.).

Study Type : OBSERVATIONAL
Estimated Enrollment : 3000 participants
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
Actual Study Start Date : 2022-06-01
Estimated Primary Completion Date : 2025-10
Estimated Study Completion Date : 2026-10

Information not available for Arms and Intervention/treatment

Ages Eligible for Study: 18 Years to 75 Years
Sexes Eligible for Study: ALL
Accepts Healthy Volunteers: 1
Criteria
Inclusion Criteria
  • 1. Participants with the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision
  • 2. Participants that have signed informed consent.
  • 3. Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information.
  • 4. Healthy participants with no clinical diagnosis of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision.
Exclusion Criteria
  • 1. Participants with primary clinical and pathological data missing.
  • 2. Participants lost to follow-up.
  • 3. Participants with too poor medical image quality to perform segment and mark ROI accurately

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

Location Details

NCT05426135


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Locations


RECRUITING

China, Hubei

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, China, 430000

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