UnknownNot Applicable

Development of an Artificial Intelligence System for Intelligent Pathological Diagnosis and Therapeutic Effect Prediction Based on Multimodal Data Fusion of Common Tumors and Major Infectious Diseases in the Respiratory System Using Deep Learning Technology.

China1,000 participantsStarted 2021-10-01

Plain-language summary

To improve accurate diagnosis and treatment of common malignant tumors and major infectious diseases in the respiratory system, we aim to establish a large medical database that includes standardized and structured clinical diagnosis and treatment information such as electronic medical records, image features, pathological features, and multi-omics information, and to develop a multi-modal data fusion-based technology system for individualized intelligent pathological diagnosis and therapeutic effect prediction using artificial intelligence technology.

Who can participate

Age range18 Years – 90 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion criteria

✓. Participants with the clinical diagnosis of lung cancer, pulmonary tuberculosis, and COVID-19.
✓. Participants that have signed informed consent.
✓. Participants \>= 18 years old and \< 90 years old.
✓. Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information.
✓. Healthy participants with no clinical diagnosis of lung cancer, pulmonary tuberculosis, and COVID-19.

Exclusion criteria

✕. Participants \< 18 years old.
✕. Participants with primary clinical and pathological data missing.
✕. Participants lost to follow-up.
✕. Participants with too poor medical image quality to perform segment and mark ROI accurately.

What they're measuring

The outcome of clinical diagnosis of suspected patients with lung cancer/pulmonary nodular (Benign/Malignant nodule).

Timeframe: 2021-2024

The outcome of clinical diagnosis of suspected patients with pulmonary tuberculosis (Positive/Negative).

Timeframe: 2021-2024

The outcome of clinical diagnosis of suspected patients with COVID-19 (Positive/Negative).

Timeframe: 2021-2024

Treatment response of anti-cancer therapy at first evaluation in patients with lung cancer/pulmonary nodules (CR, PR, PD, SD).

Timeframe: 2021-2024

Treatment response of anti-inflammation and antiviral therapy at first evaluation in patients with COVID-19 (effective/ineffective treatment).

Timeframe: 2021-2024

Treatment response of antituberculous bacilli and anti-inflammation therapy at first evaluation in patients with pulmonary tuberculosis.

Timeframe: 2021-2024

Progression free survival

Timeframe: 2021-2024

Trial details

NCT IDNCT05046366

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

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2023-12

Contact for this trial

wei geng, Phd

18696152606 wguh116@hust.edu.cn

View on ClinicalTrials.gov More Artificial Intelligence trials

Plain-language summary

Who can participate

Age range18 Years – 90 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion criteria

✓. Participants with the clinical diagnosis of lung cancer, pulmonary tuberculosis, and COVID-19.
✓. Participants that have signed informed consent.
✓. Participants \>= 18 years old and \< 90 years old.
✓. Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information.
✓. Healthy participants with no clinical diagnosis of lung cancer, pulmonary tuberculosis, and COVID-19.

Exclusion criteria

✕. Participants \< 18 years old.
✕. Participants with primary clinical and pathological data missing.
✕. Participants lost to follow-up.
✕. Participants with too poor medical image quality to perform segment and mark ROI accurately.

What they're measuring

The outcome of clinical diagnosis of suspected patients with lung cancer/pulmonary nodular (Benign/Malignant nodule).

Timeframe: 2021-2024

The outcome of clinical diagnosis of suspected patients with pulmonary tuberculosis (Positive/Negative).

Timeframe: 2021-2024

The outcome of clinical diagnosis of suspected patients with COVID-19 (Positive/Negative).

Timeframe: 2021-2024

Treatment response of anti-cancer therapy at first evaluation in patients with lung cancer/pulmonary nodules (CR, PR, PD, SD).

Timeframe: 2021-2024

Treatment response of anti-inflammation and antiviral therapy at first evaluation in patients with COVID-19 (effective/ineffective treatment).

Timeframe: 2021-2024

Treatment response of antituberculous bacilli and anti-inflammation therapy at first evaluation in patients with pulmonary tuberculosis.

Timeframe: 2021-2024

Progression free survival

Timeframe: 2021-2024