Welcome to our Cancer Detection Project using Artificial Intelligence!



Wanna Try a Cancer Detection ?

Cancer Detection

Do You Want to Know Your Probabilty to Get a Cancer? Just Have a Try!

Step 1. Blood Test Marker Values
OmegaScore
CA-125 (U/ml)
CEA (pg/ml)
CA19-9 (U/ml)
Prolactin (pg/ml)
HGF (pg/ml)
OPN (pg/ml)
Myeloperoxidase (ng/ml)
TIMP-1 (pg/ml)
Step 2. Model Selection
Model

Cancer Type Localization

Do You Want to Know Your Probabilties to Get Different Types of Cancer? Just Have a Try!

Step 1. Blood Test Marker Values
Sex
OmegaScore
AFP (pg/ml)
Angiopoietin-2 (pg/ml)
AXL (pg/ml)
CA-125 (U/ml)
CA 15-3 (U/ml)
CA19-9 (U/ml)
CD44 (ng/ml)
CEA (pg/ml)
CYFRA 21-1 (pg/ml)
DKK1 (ng/ml)
Endoglin (pg/ml)
FGF2 (pg/ml)
Follistatin (pg/ml)
Galectin-3 (ng/ml)
G-CSF (pg/ml)
GDF15 (ng/ml)
HE4 (pg/ml)
HGF (pg/ml)
IL-6 (pg/ml)
IL-8 (pg/ml)
Kallikrein-6 (pg/ml)
Leptin (pg/ml)
Mesothelin (ng/ml)
Midkine (pg/ml)
Myeloperoxidase (ng/ml)
NSE (ng/ml)
OPG (ng/ml)
OPN (pg/ml)
PAR (pg/ml)
Prolactin (pg/ml)
sEGFR (pg/ml)
sFas (pg/ml)
SHBG (nM)
sHER2/sEGFR2/sErbB2 (pg/ml)
sPECAM-1 (pg/ml)
TGFa (pg/ml)
Thrombospondin-2 (pg/ml)
TIMP-1 (pg/ml)
TIMP-2 (pg/ml)
Step 2. Model Selection
Model

Downloads

Download the executable program and demo data.

FAQ

Frequently Ask Questions.

    1. What is the cancer detection?

    The cancer detection is a model to predict the probability to get a cancer.

    2. How to condunct cancer detection online?

    There are three steps to conduct the cancer detection online:
    Step 1: Blood Test Maker Values. You need to fill out the marker values in numeric values.
    Step 2: Model Selection. You need to choose a model for prediction.
    Step 3: Submit. You need to click the "SUBMIT" button under the form. Then, the probability to get a cancer is returned to you at the bottom of the page.

    3. Is there any demo for the cancer detection online?

    Yes. We provide a demo for the cancer detection online. You can click the "AUTOFILL" button, which will fill the blood test markers with default values and choose the default model automatically. Then, you can click the "SUBMIT" button to get the result.

    4. What is the cancer type localization?

    The cancer type localization is a model to predict the probabilities to get different types of cancer.

    5. How to condunct cancer type localization online?

    There are three steps to conduct the cancer type localization online:
    Step 1: Blood Test Maker Values. You need to fill out the marker values in numeric values.
    Step 2: Model Selection. You need to choose a model for prediction.
    Step 3: Submit. You need to click the "SUBMIT" button under the form. Then, the probabilities to get different types cancer are returned to you at the bottom of the page.

    6. Is there any demo for the cancer type localization online?

    Yes. We provide a demo for the cancer type localization online. You can click the "AUTOFILL" button, which will fill the blood test markers with default values and choose the default model automatically. Then click the "SUBMIT" button to get the results.

    7. Can we conduct the cancer detection and cancer type localization offline?

    Yes. We provide the offline cancer detection and cancer type localization softwares. The softwares can be downloaded for non-commercial usage.

    8. What system does the cancer detection and cancer type localization softwares support?

    The cancer detection and cancer type localization softwares support both the Linux and Microsoft Windows systems.

About

To know something about this cancer research project.

  • Funding Support

    The work was supported by the Research Grants Council of the Hong Kong Special Administrative Region under Grants CityU 21200816 and CityU 11203217.

  • Reference

    Please be patient.
    It is coming soon ...

  • The
    End
    !

Group Members

Meet Our Group Members!

Have a Look for Their Contributions of This Cancer Detection Project!

Ka-Chun Wong

Group Leader
Manuscript Writing, Experimental Design and Implementation.

Xiangtao Li

Literature Survey.

Junyi Chen

Text Mining on Keywords and New Feature Prediction.

Jiecong Lin

Deep Learning Analysis and Feature Extraction.

Shankai Yan

High-dimensional Dataset Visualization and Analysis.

Jiao Zhang

Coding and Build the Website.

Shixiong Zhang

PPI Network and Pathway Analysis.

Contact Us


Ready to cooperate with us or have any enquiry? Give us a call or send us an email and we will get back to you as soon as possible!