The Machine Learning approach in Epigenetics

Artificial Intelligence (AI) developments have enabled many new technologies and improvements in healthcare, which have had a significant impact and have now become a routine reality. AI can now inspect medical images, analyze heart monitor results, and suggest diagnoses based on symptoms. It also brings amazing new health tech applications to end users, such as recognizing skin cancer from a single photo or calculating their age from a selfie. The stage is set perfectly for a revolution in how people interact with their health, both inside and outside the hospital.

To that end, we combine the paradigms of Machine Learning (ML) and Epigenetics to develop the Dynamic Health Score - the tool that creates a personal layer in staying healthy. By analyzing the vast amounts of data on a person's epigenetic snapshot, lifestyle, and environmental factors, EPIX provides personalized recommendations for disease prevention, early detection, and treatment. This empowers people to take charge of their health, reduces their healthcare costs, and improves outcomes. 

Machine Learning (ML) is a mathematical tool crucial to the AI revolution to the point where ML and AI are used interchangeably. The significant steps in developing powerful computer systems and the efforts of researchers have resulted in the development of a whole world of ML algorithms, either general or suited to specific tasks. These algorithms can capture highly complex, non-linear relationships in big data, resulting in previously impossible solutions or improving existing ones. Few other fields have felt the benefits of this new approach more than health- and life tech.

Epigenetics and Machine Learning have ripened as scientific fields in the past decade. Epigenetics produces enormous amounts of data that contain detailed information about your current state of health. A single strand of DNA contains millions of CPGs, each either methylated or unmethylated, and each tells a story about the lifestyle effects, ageing, and disease risks of the person it belongs to. Machine Learning mixes that information with information from phones and wearable devices, such as air pollution, physical activity, sleep schedule, etc., creating accurate, personalized predictions about that individual’s health. The result is a robust, testable measurement that can be analyzed to provide lifestyle choice insights tol optimize our clients’ healthspan.

The developments in AI have grown exponentially, every year presenting results that were unimaginable the year before. Our data science team takes pride in following those developments closely and staying at the wavefront, making sure that our algorithms bring the greatest value possible to our clients.

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