Delivering insights to the workforce to raise effectiveness and save lives
Data analysis from millions of prior emergency calls including both verbal and non-verbal data - like tone of voice and breathing patterns - enable developed AI models to look for signs of cardiac arrest.
Research from emergency departments tested emergency calls, and the impact of dispatchers receiving suggestions for questions and recommendations for actions during an emergency call. With data driven insights dispatchers showed a 93% accuracy in cardiac arrest identification. Human dispatchers alone being right only 73% of the time. An example of intelligent use of AI in real life that actually saves lives by increasing cardia arrest identification by 20%.
Machines are able to process many more dimensions of data than humans. This is the essence of augmented intelligence, insights derived from models, but human not machine- centered. Improving the human decision process in challenging situations is applicable in many more areas, such as ER doctors who have to make life-and-death decisions in minutes.
Healthcare, and other regulated industries such as Banking or Insurance are necessarily diligent at documenting their work. As with Government, States and Municipalities, all retain a treasure trove of ‘data availability’ which means sufficient, historical data for analysis and meaningful improvements throughout their practices.
AI has been in use for more than a decade, but mainly in large tech companies using their own in-house resources. That’s no longer the case, any company - not just Google, Amazon, IBM, and Microsoft and the largest enterprises- can access all the data science resources necessary to develop their own data products and AI solutions through a platform just like another web service. Data science as a service levels the playing field
Democratizing augmented intelligence by making accessible, cutting edge, end to end data science solutions for all companies.
Besides procuring off-the-shelf data enabled AI software to solve business challenges - All companies should have the ability to develop their own data models from the ground up - to benefit from their own AI intellectual property, and the advantages of independently scaling, volume and quality.
Data Science as a service positions all companies to assess each and benefit from both. Secure the future viability of your company with data enabled business models.