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Advancing Machine Learning integration with Apple ResearchKit and HealthKit

by on April 16, 2015

At BigML we are excited to announce BigMLKit, a new open source framework for iOS and OS X that blends the power of BigML’s best-in-class Machine Learning platform with the ease and immediacy of Apple technologies.

BigMLKit

BigMLKit brings the capability of “one-click-to-predict” to iOS and OS X developers in that it makes it really easy to interact with BigML’s REST API though a higher-level view of a “task.” A task is, in its most basic version, a sequence of steps that is carried out through BigML’s API. Each step has traditionally required a certain amount of work such as preparing the data, launching the remote operation, waiting for it to complete, collecting the right data to prepare the  next step and so on. BigMLKit takes care of all of this “glue logic” for you in a streamlined manner, while also providing an abstracted way to interact with BigML and build complex tasks on top of our platform.

BigML is already offering a variety of tools and libraries to make it easy to integrate BigML with whatever environment you might be working in. This includes a REST API, as well as bindings that provide a higher-lever view of it from the most popular programming languages, including PythonNode.jsObjective-C, and so on.  We also provide more advanced tools such as our powerful bigmler, a veritable command-line Swiss Army knife for machine learning, and we have many more surprises in the works that will make machine learning capabilities ever more accessible.

The introduction of HealthKit put the iPhone into the rapidly growing field of health tracking devices that can be used to monitor daily activities that impact one’s health. The Apple Watch will certainly fuel the trend towards health-oriented applications, and the recent open-sourcing of ResearchKit by Apple is providing further momentum for this to extend into medical research.

All of this surely creates a powerful constellation, but it leaves behind a key factor which is not included in the solution that Apple provides with HealthKit and ResearchKit: an easy way to make sense of the collected data. This is where BigML is happy to enter the picture with BigMLKit, which we believe will be a key enabler for a new class of applications in health care and medical research that will empower researchers, doctors, hospitals and health professionals to learn from health data collected via HealthKit and ResearchKit.

BigMLKit thus reaffirms BigML’s commitment to enable new machine-learning-powered applications on any platforms – and adds a special focus on the Apple ecosystem, where the combination of  existing and emerging devices and solutions (such as the iPhone, HealthKit, Apple Watch and ResearchKit) is promising to revolutionize health care and health research.

BigMLKit is still a very young project that can be found on GitHub. We welcome your feedback and we really appreciate your pull requests. Stay tuned for more updates, including a follow-up post with more information about the way you can integrate BigMLKit in your app.

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