Future of Health Monitoring and Diagnosis

To be a bit of a provocateur, I start by saying that current medical science does not differ that much of medieval. This is based on my experiences while working within medical research. I am not a MD, but data scientist, bioinformatician, mathematician and computer scientist. From my point of view, medical science seems mostly an art of educated guessing, and it usually comes into play when symptoms of some disease are already evident.

Considering that we live in the age of highly complex information systems, our health is still monitored by medieval methods. Much more effort has been done to monitor our social networks in Facebook, Google+ and Twitter, and complex databases and business intelligence systems analyse our habits as consumer of commercial commodities. But our health is not monitored at all, or only with very crude methods.

Lets make a comparison. Business intelligence systems have analysed all purchases on retail stores and on-line stores. Not only your purchases but all other customers buying habits, too. On-line stores also know every item that you browsed, but did not purchase. Based on all that data, some social demographics and other statistics, it can predict quite well what you may purchase in the future and what kind of items you are interested in.

But considering your health, there is no generally available system that could predict the progression or decline of your health. Usually, you go to the doctor when you are feeling ill and the symptoms are self-evident. Considering that we have lots of technology, data and methodology, I think it is a disgrace.

But it can change. We have been developing a system that will solve this problem using modern, massive Big Data solutions and Data Science tools to collect and analyse data. System itself can collect data from various sources like other databases, OCR documents, questionary forms etc. System can also collect data from smartphones and mobile diagnostic devices. In addition, biosamples may be analysed and that laboratory data used for more accurate picture.

Based on data described above, the system can create models to predict the progression of health for any individual. Although the data is more complex and non-structural, the case is very similar to business intelligence behind customer analysis. Obvious benefits are that the system can monitor all possible diseases simultaneously, and it does not forget old details.

My vision is, that with this kind of system in widespread use, we could notice many diseases during very early on-set. Or we could find out a serious risk even before on-set of the disease in question. This could decrease the costs to treat a chronic or long-term disease by giving options to prevent the on-set of disease or to keep the symptoms at mild stage.


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