ABOUT CYBALIFE

Cybalife tackles severe problems and provides a complete diagnosis for chronic conditions with the ability to perform huge computations and manipulate omics and electronic health record data. The multi-omics analysis allows the identification of associated factors from different biological processes. Such as gene expression, protein synthesis, and post-translational modifications, cellular metabolic processes, glycosylation, etc., By maximizing the available information to increase the possibility of identifying the root causes of disease.

And the addition of an electronic health record (EHR). Real-time, patient-centered records that contain details of the medical history, medications, allergies, radiology images, treatment plans, and laboratory results of patients. It will allow effective diagnoses of patients, reduces medical errors, and provides safer care. The process is crowded with technology that enables machines to solve many complex decision-making tasks.

Cybalife is a three-variation solution. One of them is that of the smartphone as a mobile application. Cybalife leverages mobile sensors to provide a point of care (POC). The POC will allow easy generation of diagnostic results quickly so that appropriate treatment can be implemented, leading to an improved clinical or economic outcome.

In general, Cybalife has one of its roots in the epidemiological modeling approach, such as SIR, SEIR, and SEAICRloop. Epidemiological modeling uses mathematical, statistical, and computational tools to study the spread of infectious pathogens in host populations. It uses data and hypotheses describing the demographic processes, environmental characteristics, transmission opportunities, and health consequences of diseases. It has been used to characterize risks. For instance, forecasting COVID-19 and its impact on healthcare supports and justifies the adoption of measures, guides the optimal deployment of vaccines, and informs many aspects of our lives with the virus.