Upload MRI to detect brain tumors
Answer medical questions using ClinicalBERT
Upload EEG data to classify signals as Normal or Abnormal
Generate disease analysis from chest X-rays
Consult symptoms and reports with AI doctor
Ask medical questions and get answers
Predict diabetes risk based on medical data
Classify and assess severity of lung conditions from chest X-rays
Consult medical information with a chatbot
Upload MRI to detect tumors and predict survival
Analyze lung images to identify diseases
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Flask is a micro web framework written in Python. It is lightweight, flexible, and ideal for building small applications or APIs, particularly in the Medical Imaging domain where it can be used for tasks like MRI analysis to detect brain tumors.
• Lightweight: Flask has a small codebase and is easy to use without unnecessary features. • Flexible: It supports extensions and is highly customizable for various application needs. • Modular: Built with a modular design, Flask allows developers to build applications in a structured manner. • Unit Testing: Flask comes with built-in support for unit testing, making it developer-friendly. • RESTful API Ready: It simplifies the creation of RESTful web services.
Using Flask involves a few simple steps:
pip install flask in your terminal.from flask import Flask
app = Flask(__name__)
@app.route("/")
def home():
return "Hello, Flask!"
app.run().1. How do I install Flask?
Flask can be installed using pip: pip install flask.
2. Is Flask suitable for building large enterprise applications?
Flask is best suited for small to medium-sized applications. For large enterprise applications, Django might be more appropriate.
3. How can I handle large MRI files in Flask?
To handle large MRI files, use streaming uploads or background processing to ensure efficient memory usage and performance.
4. Are there extensions available for Flask?
Yes, Flask has a wide range of extensions for databases, forms, caching, and more, which can be easily integrated into your application.