Artificial Intelligence in Healthcare and Research

The health-care industry is transitioning into a modern, tech-driven landscape that is focusing primarily on the collection and analysis of big data. Currently, we are at the cusp of a tech revolution, where data is collected and processed in order to influence and change user behavior; the health-care industry is yet to catch up to the advancements made in other industries. The most common question that individuals across industries ask is: how can Artificial Intelligence (AI) be best utilized to collate, analyze, and store large pools of data? In fact, this will be one of the main topics of discussion at the 2019 World Summit AI conference in Montreal (April 10-11).

This year’s agenda of the Summit features groundbreaking presentations in business and science, with major AI announcements, panel discussions, and notable focus on “#AI4Good”. The message is simple: deep learning technology and machine learning are being utilized to have a positive social, economic, and ecological impact. For the health-care industry in particular, the efficient collation and processing of data will be critical if such a social impact is to be achieved.

The data fragmentation problem

The availability of large data-pools is enabling rapid progression in research that can then be absorbed and adapted into new technologies. Currently, however, patient data is collated in a somewhat arbitrary manner; this costs money and time and increases the chance of inaccuracies and gaps in patient-records and diagnosis. Clearly, this is the perfect avenue for machine learning and AI, seeing how there is a pressing need in the market to gather, streamline, and process patient and health-care data.

AI exceeds

It is an accepted fact that AI technology exceeds certain human capabilities, at least in the context of diagnostics and prevention. While data fragmentation presents a barrier to an effective prevention-based, proactive approach to health-care, revolutionary Platforms like Playpal are addressing this market-gap with their proprietary technology that builds on users’ health capital (check our Health capital blog post). More specifically, Paypal represents a step toward proactive aggregation of data from all kinds of health databases to give users meaningful and customized insights on their health data. By creating a decentralized data repository for the device market, the Platform ensures interoperability, integration, correlation, standardization, and normalization of health information.

Evidently, tools for better data management in health-care do exist, it is just a matter of when the issue of data fragmentation will get resolved. Playpal marks one such step toward an organised solution.

Learn more about the Americas World Summit here.