YOULLDIE

Executive Summary

youlldie is an open-source, data-driven, AI-powered app that statistically predicts life expectancy. Specifically, it determines the risk of death from different causes based on inherited risk factors, environment and lifestyle choices. The app enables efficient decision-making and solves several immediate problems in the healthcare, life insurance, financial planning and wealth management industries. The app also aims to incite users to adopt healthy lifestyles. This project makes the app’s source code fully transparent and aims to gather input from the open-source community to improve the algorithm's accuracy. This project also aims to build a data lakehouse comprising mortality data from global healthcare systems to make the app totally data-driven, accurate, and relevant to the world's population.

How the app works

The app is currently available at https://youlldie.com

Users enter risk factors into the apps. Specifically, without any input, the apps provide the life expectancy of the world's population. Every input refines the life expectancy prediction to a more specific population, down to the individual level.

Mission

This project’s mission is to improve global life expectancy by optimizing health-related decision-making with data-driven solutions. The goal is to create a global mortality data lakehouse and develop an app that can predict life expectancy based on the data compiled in the lakehouse. The idea behind the project is that metrics are powerful enablers of improvements, and life expectancy can be improved if it can be predicted accurately.

Problems Addressed

Inaccurate life expectancy prediction model

Predicting life expectancy is complex. It must consider many factors to be accurate and useful. For example, gender, race, world region, education, income, alcohol use, tobacco use, physical activity, sleep, blood pressure, body mass index, medical history and family medical history are important factors that impact life expectancy. Currently, no life expectancy model can account for all those risk factors. Thus, their accuracy is questionable. Moreover, no life expectancy algorithm is actualized with current data. As such, they fail to account for the ever-changing global context, including social behaviours, epidemics, climates, industrial hazards, and geopolitical risks.

Ineffective life expectancy prediction tool for the general public

No accurate life expectancy prediction tool is available to the general public. People must thus rely on guesswork riddled with cognitive biases to assess their life expectancy. As such, the general public can hardly estimate their life expectancy and make informed decisions about their future when planning their finances and managing their wealth. Furthermore, health authorities have never effectively conveyed the impact of different risk factors on life expectancy to the general public. Public health warnings are often undermined by cognitive bias in individuals who are misinformed or consider themselves an exception to the rule. For example, many consider alcohol harmless or even good in moderation, whereas the scientific community agrees that there is no safe amount of alcohol.

Unavailability of structured worldwide mortality data for research

The multifactorial nature of life expectancy cannot be fully understood without holistically assessing the impact of all risk factors on all causes of death. Unfortunately, no standardized worldwide mortality data pool exists to allow for this. As such, solid conclusions about global life expectancy can hardly be drawn.

Solution Offered

The youlldie app can account for an unlimited number of risk factors and their interactions. Also, with the development of a global mortality data lakehouse, the app can be data-driven by the most current global mortality data. As such, the app has the potential to be the most accurate life expectancy prediction tool available. It can foster a realistic understanding of risks to life expectancy and contribute to better decision-making related to life choices. Indeed, it can lead to a better appreciation of life in general. Moreover, by leveraging a global mortality data lakehouse, the app has the potential to make predictions beyond current scientific knowledge and act as a beacon to orient further research.

Emerging Opportunity

Global mortality data holds invaluable information that can be used to improve global health. Moreover, modern data communication and warehousing capabilities allow the pooling of global mortality data into a structured data lakehouse. Such data lakehouse would make it possible to train a statistical model that can predict life expectancy with unprecedented accuracy and roll it out as a decision-making supporting tool. The potential of such data lakehouse and life-expectancy prediction tools is great and spans many industries. Specifically, an accurate life expectancy prediction tool can support health-related decisions made by healthcare professionals, researchers, insurance providers, financial advisors, and the general public. As such, developing a life expectancy prediction tool capable of leveraging global mortality data represents an opportunity to make the world population generally healthier.

Market Segmentation

Healthcare

Knowing a patient's potential life expectancy can help healthcare professionals tailor personalized interventions and preventive care. Specifically, a life expectancy prediction tool can help healthcare providers provide targeted interventions for conditions that most impact patients' life expectancies.

Moreover, a life expectancy prediction tool can optimize the implementation of public health programs. Specifically, it can improve the effectiveness of resource allocation and ensure that individuals with potentially shorter life expectancies receive appropriate care. Finally, accurate life expectancy predictions can sensibilize the population to health risks and reduce early death and associated costs. As such, a life expectancy prediction tool can improve healthcare systems' efficiency.

Health Research

For health and socio-economic researchers, a data lakehouse comprising global mortality data represents a valuable source of information for guiding research. Moreover, a life expectancy prediction tool can help researchers better understand population health trends, disparities and factors influencing longevity.

Life Insurance

For the life insurance industry, an accurate life expectancy prediction tool improves risk assessments and allows companies to offer fair and balanced insurance products. This confers a competitive advantage as it allows insurance products to be provided to a broader audience while reducing losses. This can translate into improving global health as more people get coverage for the treatment and care they need while reducing the burden on the payers.

Financial Planning and Wealth Management

Knowing how much time one has left is of great value for any long-term commitment. Specifically, for financial planning and wealth management, a life expectancy prediction tool can help answer the question "When do you plan to retire?" which is central in determining how much one needs to save and invest to ensure sufficient funds throughout retirement. Furthermore, for estate planning, predicting one’s life expectancy allows one to plan responsibly and ensure the well-being of loved ones. As such, a life expectancy prediction tool conveys a competitive advantage to financial planning and wealth management companies as it can serve as a crystal ball to help determine when major life milestones, such as starting a family and retiring, should occur. This allows financial planning and wealth management companies to assess their clients' financial needs more accurately and make their offers more attractive.

Wellness

For wellness management, a life expectancy prediction tool can provide a realistic perspective of death that can improve lifestyle choices. It can, for example, present incentives for adopting healthy lifestyles. This, in turn, can improve quality of life and reduce the risk of preventable deaths. As such, a life expectancy prediction tool can help users fully appreciate the value of healthy habits.

Objectives & Milestones

The algorithm behind the app was built based on information gathered from peer-reviewed literature and public databases. As such, the app's output aligns with the current scientific knowledge. The app was also built to be data-driven and be able to "learn" from current mortality data.

The next step is to build a data lakehouse comprising global mortality data. The accumulation of this data will serve to gradually improve the app's accuracy and relevance to the world's population.

For the first year, the goal is to establish a proof of concept that mortality data can be used to train an algorithm to predict life expectancy. For the second year, the goal is to demonstrate that the algorithm has value for strategic decision-making about patient care, insurance coverage, financial planning, wealth management and lifestyle choice. As such, the following key milestones are set over the first two years:

Year 1

• Objective 1: Gain access to mortality data from a major healthcare system.
• Objective 2: Establish a standardized framework for acquiring data from global health providers.
• Objective 3: Execute machine learning to improve the app’s predictive power and usefulness.
• Objective 4: Validate the app's ability to predict life expectancy with a 90% accuracy.
• Objective 5 / Milestone: Publish a proof of concept (POC) article in a peer-reviewed scientific journal describing the app and the outcome of one year of machine learning.

Year 2

• Objective 6: Gain data access to mortality data in major economies (USA, UK, EU, Japan). *Objective 6: Gain endorsement from high