In recent years, we’ve seen a number of healthcare-focused developers emerge that provide HIPAA-compliant health app development as well as cloud-based data management and analytics. We’ve covered some of Medable’s work with a ResearchKit app focused on patient’s with LVADs as well as a virtual care clinic. They also recently launched Axon, a do-it-yourself platform for development of ResearchKit apps.
As health apps collect ever increasing types and volumes of data on individuals, a core challenge is how to analyze that data and generate actionable insights that can improve patient care. That’s what Medable’s Cerebrum platform aims to help with it.
Cerebrum is a cloud-based machine learning tool for healthcare apps that helps analyze the mountains of patient generated data to try to improve prediction of health events so that we can intervene sooner. According to Medable,
Cerebrum provides machine learning across the ecosystem of clinical study data, including standard clinical instruments and patient reported outcomes data, meta-data from mobile devices, connected devices, and genomic and epigenomic data…Cerebrum’s unique machine learning system has the ability to automate the identification of high-value predictors and provide rapid generation of novel insights…Cerebrum can help [healthcare providers] gain a much better understanding of their data through text classification and mining, emotion/behavior analysis, tagging, and other health-specific features.
Cerebrum is currently being piloted by some of the healthcare institutions with whom Medable works. It will be interesting to see if this platform helps translate the data generated by some of the large digital cohorts, whether through ResearchKit or independent studies like Health eHeart, into learning models that can be applied outside of those studies.