The Personicle: A glimpse into your future

This article is based on the ideolog of Dr. Ramesh Jain’s work on Personicle. To find out more please visit the Personicle. 

 Current healthcare employs reactive measures rather than proactive ones, causing delay in diagnosis and prolonged treatment.

We now have the capability to access large volumes of high-quality data from multiple personal, social, and environmental data streams.

This data can enable intelligent insight generation for high precision medicine and personalized healthcare.

Based on this theory, Dr. Ramesh Jain, Professor in information and computer sciences at University of California, Irvine, conceived the personicle model for individualized proactive healthcare.

The personicle model is a personal chronicle. It is a log of all personal, socialmedical, and environmental events and information associated with a specific person. But it is not just a collection of data; it differentiates itself other models based on two important attributes.

It is built for human-understandability, therefore the information gathered is presented in a manner that everyone can interpret and benefit from. Additionally, it has incredibly accurate predictive power and informs the future implications of an individual’s current health state.

Before exploring the use cases, lets understand the fundamental aim.

The Personicle’s Distinctive Features:

It is a model of a specific person shaped by assimilating multiple data streams. The model is meant to be interactive that invites users to engage and document their health logs, and relays predictions information to users based on this information.

The predictive function allows the model to simulate events and report their outcomes and consequences.

The intent of running simulations through personicle is to prevent unfavorable outcomes and encourage positive behavioral changes for better health outcomes.

Each personicle is compatible with multiple applications as well that act as additional data sources. The algorithm is able to extract relevant information for running precise simulations and presenting accurate predictions.

Adapting Personicle for Healthcare:

By adapting personicle for healthcare, two important aspects will be covered. Firstly, accurate prediction will help map out the progression of certain diseases in patients.

Secondly, treatment processes will be more inclusive for patients with the personicle’s ability to explain causality between their actions/decisions and the impact on their health.

The personicle is also a natural fit in the way future healthcare techniques are shaping up. Nowadays, healthcare professionals have a variety of data from advanced medical apparatus as well as everyday wearable gadgets to monitor patient health.

The personicle is the perfect engine to consolidate this data using AI, ML and other analytical approaches.

It also presents the outcome in a desirable fashion. With these capabilities at its core, the model’s applications in healthcare are truly promising.

Personicle Users in Healthcare Industry:

In the healthcare industry personicle works at a service level as well as an administrative level. There are three types of users who can benefit from it.

  • Patients themselves are the main beneficiaries. Individual users can interact with their personicle models to learn about their state of health. It becomes easier to follow treatment plans as their personicle model simulates and presents the positive effect the treatment will have on their health. Patients volunteer medical and geographical data to the personicle which consequently uses them to create more realistic models and precise predictions.
  • Healthcare professionals are another group who can extensively use personicle to upgrade their services. Healthcare providers will be able to provide personalized treatment plans and map recovery journeys much better with the personicle’s. They will benefit from the analysis and prediction of the personicle which will aid them in diagnosing and remedying certain diseases. Personicle will also help employers in improving employee performance through accurate performance analysis. Health insurance providers could use personicle models to generate financial streams for individual patients using its predictive capabilities.
  • Application Developers who work with integration tools and data analysis will be able to use personicle as the epicenter of data consolidation and analysis. Hence, they will be able to shape the user journey and naturally integrate each health monitoring application to the personicle.

Personal Models for Secure Data:

The personicle’s virtual infrastructure relies on the collection and processing of high volumes of data. In healthcare, this involves sensitive data such as personal medical and financial records of patients, confidential information between healthcare professionals and patients and access to a large database of individuals seeking insurance/medical treatment.  

To safeguard this data, personicle technology designates users as the primary owners of their data. Therefore, users have control over permissions for who has access to that data and its nature.

The users can monitor and control how the personicle model uses their data and share it only with trusted parties. In this manner, personicle makes data much more secure than conventional data collection from other mechanisms. 


This modern AI model brings unique advantages in the form of human-understandability, superior predictive power, and confidentiality, making it worth investing. However, to effectively develop this model’s various components, we need more research and precise personalized data. 

Psychologists, social scientists, AI services companies, and healthcare communities are working together to develop this revolutionary model inspired by advances in technology, business and social models.  

Share Now:

Let's make it happen

We love fixing complex problems with innovative solutions. Get in touch to let us know what you’re looking for and our solution architect will get back to you soon.