RiskFix: A Modular Package for Visual-Interactive Validation of Risk-Prediction Machine Learning Models

This is a React component library that provides reusable UI components for building web applications.

Installation

You can install this library via NPM by running the following command:

npm install riskfix

Usage

To use this component library in your project, you can import individual components like so:

import { PreBias } from "riskfix"

function MyComponent() {
	const [count, setCount] = useState(0)
	return (<PreBias setPrebiasValue={setCount} />);
}

Available Components

PreBias: A pre-bias component

• setPrebiasValue: (value: number) => void;

QRReader: A QR code reader component

• bedside_info: string;
  • A string representing the information about the bedside monitoring device.
• bedside_devices: string | null;
  • A string or null value representing the list of devices connected to the bedside monitoring system.
• setBedsideDevices: React.Dispatch<React.SetStateAction<string | null>>;
  • A React state hook function that takes a string or null value and sets the bedside devices.
• setBedsideInfo: React.Dispatch<React.SetStateAction>;
  • A React state hook function that takes a string value and sets the bedside info.
• handleScan: (data: any) => void;
  • A function that takes a data object as an argument and is called when a QR code is successfully scanned.
• handleError: (err: any) => void;
  • A function that takes an error object as an argument and is called when there is an error with the QR code scan.

PredictionTimeline: A prediction timeline component to show model validated results.

• prebiasValue: number | undefined;
  • An optional number value representing the pre-bias value for the risk prediction model.
• bedsideDevices: string | null;
  • A string or null value representing the list of devices connected to the bedside monitoring system.
• bedsideInfo: string;
  • A string value representing the information about the bedside monitoring device.
• user: { email: string } | undefined;
  • An optional object with an email property representing the user information.
• recordValidation: (val: IValidation) => Promise<number | undefined>
  • A function that takes a validation object as an argument and returns a promise that resolves to a number or undefined value.
• fetchAnnotation: (user: string, devid: number, start_time: number, end_time: number) => Promise
  • A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to an annotation object.
• recordAnnotation: (val: IRecordAnnotation) => Promise<number | undefined>
  • A function that takes an annotation object as an argument and returns a promise that resolves to a number or undefined value.
• fetchPrediction: (devid: number, limit: number, start_time: number, end_time: number) => Promise
  • A function that takes devid, limit, start_time, and end_time as arguments and returns a promise that resolves to a prediction scores object.
• fetchValidation: (user: string, devid: number, start_time: number, end_time: number) => Promise
  • A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to a validated scores object.

Timeline: The timeline visualization component used within the PredictionTimeline component.

• devid: number;
  • A number value representing the ID of the monitoring device.
• prebias: number;
  • A number value representing the pre-bias value for the risk prediction model.
• modelPause: boolean;
  • A boolean value indicating whether the model is paused or not.
• user: string;
  • A string value representing the user information.
• fetchInterval
  • The time of the interval between points, in milliseconds. An example value would be: 30000 for 30 second intervals.
• timeWindow
  • The size of display window in terms of time, in milliseconds. For example, if we wanted to show the last 5 mins. we would put in: (5 * 60 * 1000).
• rollbackTime
  • If a time rollback is required from the latest set of points, use this to start after a certain number of milliseconds before the current time within the model values.
• fetchPrediction: (devid: number, limit: number, start_time: number, end_time: number) => Promise
  • A function that takes devid, limit, start_time, and end_time as arguments and returns a promise that resolves to a prediction scores object.
• fetchValidation: (user: string, devid: number, start_time: number, end_time: number) => Promise
  • A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to a validated scores object.
• recordValidation: (val: IValidation) => Promise<number | undefined>
  • A function that takes a validation object as an argument and returns a promise that resolves to a number or undefined value.

Contributing

To contribute to this project, please follow these steps:

Fork the repo Create a new branch (git checkout -b my-new-feature) Make changes and commit (git commit -am 'Add some feature') Push to the branch (git push origin my-new-feature) Create a new pull request

License

This project is licensed under the MIT License. See the LICENSE file for more details.