Predictive analytics is the next frontier in medicine. Today, patients with chronic medical conditions suffer life-threatening disease complications without warning. Tomorrow, patients and healthcare providers will use Transformative tools to identify the subtle physiologic changes that precede symptom onset, enabling personalised preparation and prevention.
We apply world-class machine learning techniques to healthcare, a sector that continues to apply twentieth century technology to data interpretation. The nexus of non-invasive continuous monitoring technologies, cloud-based data transmission, and advanced computing holds the power to transform healthcare. We harness these tools to empower patients and healthcare providers to avoid disease complications, saving lives.
Our initial focus: Sudden Cardiac Arrest
Globally, 6 million people per year suffer a ventricular tachyarrhythmia, causing Sudden Cardiac Arrest, of whom only one percent survive. Without steady blood flow providing oxygen to the brain, death typically ensues within minutes.
Rapid defibrillation provides patients the best chance to survive. Of patients who suffer a Sudden Cardiac Arrest in a US hospital, survival-to-discharge jumps from 15 percent among those who are defibrillated more than five minutes after arrest and to 39 percent for those who are defibrillated in less than one minute.
No current technology warns patients or healthcare providers of an oncoming arrest. Instead, bystanders or healthcare providers rush to begin delivering CPR and preparing for defibrillation only after blood has stopped flowing to the brain, worsening both mortality rates and long-term neurological function among survivors.
J Electrocardiol. 2007 Nov-Dec, 40(6 Suppl):S118-22
 N Engl J Med 2008; 358:9-17