If we can collect enough data on the population, illnesses could be curbed. Presently, though powerful, supercomputers are not up to the job that will be required of them in the future. Enter quantum computers and their partner, Machine Learning
The ability to collect data quickly and easily in the global health industry can save lives when we’re talking about those at risk. Big data will inevitably play a vital part in achieving this. Datasets in pharmaceutical research can, if conducted properly, ameliorate countless people’s health issues and give us a vast amount of information we can use to stop the spread of diseases.
These data sets can be exploited to predict patients whose chances of being readmitted to hospital are high after initial treatment, as well as being able to make a prognosis on the best approach concerning the treatment once they have been readmitted to hospital. This predictive intelligence could save millions of lives and state treasuries a fortune.
A win-win all round.
Currently, the supercomputers at hand for the task are limited to how much they can cope with.
An amalgamation of artificial intelligence (AI), machine learning (ML) and quantum computing (QC), on the other hand, could potentially handle all this much better.
The case seems to be then, whoever can find fast, cost-effective ways of utilizing proprietary QML and ML algorithms, harness that power into an augmented intelligence system that can collect, sort and diffuse the data into meaningful insight, will have a valid business model for the 21st century.
One startup, Toronto-based Netramark Corp, thinks it has a solution to the patient dataset problem.
‘EXPLAINABLE COGNITIVE TECHNOLOGY: CLASSICAL AND QUANTUM ML FOR COMPLEX DATA’
— Netramark Corp
The brains behind it all, CEO and co-founder Dr. Joseph Geraci, a Canadian mathematician, medical scientist and quantum machine learning specialist, believes Netramark Corp has ‘created a system that has proven itself to be great at cracking open disease and explaining what is going on within each subtype that it discovers’.
Founded in 2015, Netramark Corp has solutions for pharmaceutical companies that have problems with clinical trials by utilizing tools like its Netraplay, a ‘data microscope’, NetraAI, a ‘quick learning tool on smaller datasets’ and Deep Crush, an ML tool that can make sense of any variable inputted into the system, no matter what the complexity of the dataset. These are complemented by the Agile ML tool.
‘AI IS WHAT IS AVAILABLE…AND THE IMPACT IT WILL HAVE ON OUR HEALTH CARE IS MASSIVE.’
— Dr. Joseph Geraci
By Geraci’s side is his COO Richard Brooks. By day a serial entrepreneur and business lawyer, he has been involved in the startup scene in Canada for over two decades. His acumen will, like Geraci’s, be valuable moving the startup into new areas of development.
The abilities inherent in QML and ML could anticipate outbreaks while, at the same time, forecast its behaviour. Once patterns are established, the data could then be systemized and collated universally and made accessible to hospitals/medical institutions globally via consensus, establishing a rapid-response force to future pandemics.
‘WE CAN TRAIN A MACHINE TO BE ABLE TO MAKE PREDICTIONS ABOUT AN OBJECT WHICH, IN TURN, GIVES US HUMANS THE POWER TO FORECAST THE FUTURE.’
— Dr. Joseph Geraci
This scenario, however outlandish it appears, could save innumerable lives and give us a good night’s sleep.
Netramark Corp’s finger is on the pulse of the latest pharmaceutical and biotech developments. I’m sure we will be hearing more from this Canadian startup soon.