## Data Story

It was a project about chest cancer detection using machine learning and deep leaning (CNN) .

we classify and diagnose if the patient have cancer or not using AI model .

We give them the information about the type of cancer and the way of treatment.

we tried to collect all data we need to make the model classify the images easily.

so i had to fetch data from many resources to start the project .

I researched a lot to collect all the data from many resources and cleaned it for the CNN .

## Data

Data contain 3 chest cancer types which are Adenocarcinoma,Large cell carcinoma, Squamous cell carcinoma , and 1 folder for the normal cell

Data folder is the main folder that contain all the step folders

inside Data folder are test , train , valid

test represent testing set

train represent training set

valid represent validation set

training set is 70%

testing set is 20%

validation set is 10%

### Adenocarcinoma

Adenocarcinoma of the lung: Lung adenocarcinoma is the most common form of lung cancer

accounting for 30 percent of all cases overall and about 40 percent

of all non-small cell lung cancer occurrences. Adenocarcinomas are

Adenocarcinomas of the lung are found in the outer region of the lung

in glands that secrete mucus and help us breathe.

Symptoms include coughing, hoarseness, weight loss and weakness.

### Large cell carcinoma

Large-cell undifferentiated carcinoma: Large-cell undifferentiated carcinoma lung cancer grows and spreads quickly and can

to 15 percent of all cases of NSCLC.

Large-cell undifferentiated carcinoma tends to grow and spread quickly.

### Squamous cell carcinoma

Squamous cell: This type of lung cancer is found centrally in the lung,

where the larger bronchi join the trachea to the lung,

or in one of the main airway branches.

Squamous cell lung cancer is responsible for about 30 percent of all non-small

cell lung cancers, and is generally linked to smoking.

## Acknowledgements

We wouldn't be here without the help of others and the resources we found.

thanks for all of my team and the people who supported us