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Development and study of generalized model for artificial intelligence disease screening and diagnosis based on multi-omics information fusion

Development and study of generalized model for artificial intelligence disease screening and diagnosis based on multi-omics information fusion

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400081249
Enrollment
Unknown
Registered
2024-02-27
Start date
2024-02-27
Completion date
Unknown
Last updated
2024-07-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast and lung diseases

Interventions

Gold Standard:Pathologic diagnosis based on a biopsy surgery or therapeutic surgery, or a follow-up record that is at least greater than 6 months old.
Index test:1. General clinical information that includes tumor size, BMI, etc
2. Radiomics features of multi-modal multi-temporal imaging and optical examinations, multi-modal examination types including ultrasound, color doppler, elastography, mammogram, MRI, chest CT, 3D Opti
3. Metabolomics, genomics, transcriptomics, proteomics, lipidomics, Raman spectroscopy and other histological information of blood, exhaled gas, saliva, urine and stool specimens
4. Metabolomics, genomics, transcriptomics, proteomics, lipidomics, Raman spectroscopy, etc. of the cancerous tumor and the fresh tissue next to the cancer
5. Pathohistology and Raman spectroscopy information of paraffin HE-stained sections of cancerous and paraneoplastic tissues.

Sponsors

The First Affiliated Hospital of Anhui Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
1 Years to 100 Years

Inclusion criteria

Inclusion criteria: 1.Patients with breast disease, patients with lung disease, patients with both breast and lung disease and normal population; 2.Those who have undergone multi-modal ultrasonography, mammogram, MRI, chest CT, DOT optical imaging, Raman spectroscopy and other single or multi-omics examinations before biopsy or surgical treatment, and whose original image data are complete, and the image pictures are clear in line with the quality requirements of deep learning analysis; 3.Clear pathologic results obtained by puncture biopsy, surgical biopsy, or a follow-up record of at least greater than 6 months; 4.Patients with complete clinical information and general demographic information.

Exclusion criteria

Exclusion criteria: 1.Patients who underwent biopsy procedures such as VAB, mastoidoscopy, lumpectomy, and intra-operative freezing prior to the relevant imaging examination, i.e., patients whose lesions were already removed from the body when the examination was done; 2.Those with poor image quality of relevant imaging examinations, with artifacts or partial loss of images; 3.Those with incomplete patient information and case data.

Design outcomes

Primary

MeasureTime frame
age;Menstrual status;Personal Cancer History;Family history of cancer;mastalgia;BMI;nipple discharge;Mass size;BI-RADS;Radiomic features;Pathomics features;Raman spectra;Genomics;Proteomics;Metabolomics;Transcriptomics;Mammogram breast density types;Biopsy Method;benign and malignant;Histological type;Molecular subtypes;Lymph Node Status;Neoadjuvant treatment programs;Surgical method;Whether or not pCR;Adjunctive therapy programs;survival status;postoperative recurrence;Accuracy;Sensitivity, SE;Specificity, SP;Positive predicative value, PPV, PV+;Negative predictive value, NPV,PV-;AUC;Hosmer-Lemeshow goodness-of-fit;follow-up time;hemoglobin concentration;Hematology Indicators;Tumor indicators;Immunocyte indicators;Cause of death;nation;marital status;

Secondary

MeasureTime frame
Location;Distance to nipple;Calcification;lipidomics;Immunomics;glycomics;

Countries

China

Contacts

Public ContactPei Jing

The First Affiliated Hospital of Anhui Medical University

peijing@ahmu.edu.cn+86 139 6666 8272

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026