Sigmoid activation function for logistic regression

Verify Bayesian posterior stability across symptom order permutations.

Initialize validation error. Args: message: Error message field: Field that failed validation **

Initialize not found error. Args: resource: Resource type (e.g., 'Disease', 'Patient') resource_id: Resource

Initialize unauthorized error.

Initialize forbidden error.

Initialize rate limit error. Args: retry_after: Seconds until retry is allowed

Initialize prediction error. Args: message: Error message model_name: Name of the model that failed

Initialize error handler. Args: app: Flask application instance

Initialize rate limiter with configured backend selection.

Initialize security validator.

Initialize structured logger. Args: name: Logger name log_dir: Directory for log files

Initialize request logger. Args: app: Flask application instance

Get adjusted threshold for disease prediction. Uses class-specific thresholds to balance sensitivity vs specificity. For critical di

Flask app bound to an isolated SQLite DB. Windows-safe teardown: - close the mkstemp file handle immediately (otherwise it holds a

Create and configure a test application instance with an isolated SQLite DB.

Apply ensemble voting to reduce false negatives. Combines multiple models: Naive Bayes, Random Forest, SVM. Prediction: "positive" i

Create an authenticated test client.

API endpoint that returns the full bias analysis as JSON. Used by the dashboard frontend to populate charts and tables.

Render the bias analysis dashboard page.

Calculates the posterior probability using Bayes' Theorem for ML models.

Calculate log-odds contribution of each symptom.

Calculate posterior probability based on diagnostic test result.

Check if rollback is possible.

API endpoint to handle chatbot messages. Expected JSON payload: { "messages": "History of chat" }

Create test client with test database

Create a test client.

Compute 95% confidence interval using bootstrap resampling. Returns {point, lower, upper, confidence_level}

Decorator to add CORS headers to response. Example: @app.route('/api/data') @cors_headers def get_data():

Log critical message.

Display the posterior probabilities.

Render the doctor dashboard page

Generate edge cases for model testing.

Create a standardized error response. Args: message: Error message status_code: HTTP status code **kwargs: Additiona

SHAP-based prediction explainability endpoint.