In this section, we have used a simple RandomForestClassifier to diagnose the breast cancer.

Creating the flask API

app = Flask("__name__")

The loadPage method calls our home.html.

@app.route("/")
def loadPage():
	return render_template('home.html', query="")

The cancerPrediction method is our POST method, which is basically called when we pass all the inputs from our front end and click SUBMIT.

@app.route("/", methods=['POST'])
def cancerPrediction():

The run() method of Flask class runs the application on the local development server.

app.run()

Yay, our first model is ready, let’s test our bot. The above given Python script is executed from Python shell.

Go to Anaconda Prompt, and run the below query.

python app.py

Below message in Python shell is seen, which indicates that our App is now hosted at http://127.0.0.1:5000/ or localhost:5000

* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

HERE'S HOW OUR FRONTEND LOOKS LIKE:

FOR DIAGNOSED, WE ARE ALSO SHOWING THE PROBABILITY/CONFIDENCE SCORE:

FOR NON DIAGNOSED, WE SIMPLY RETURN THAT "THE PATIENT IS NOT DIAGNOSED BY BREAST CANCER"