Objectives of the service
This solution focuses on leveraging advanced technologies to revolutionize diagnostics and health management.
The platform integrates satellite measurements, earth observation data, and medical insights to generate
valuable diagnostic suggestions and predict broader health impacts. Current health and crisis response systems
are challenged by unpredictability and inadequate preparedness for the indirect public health impacts of natural
events. This leads to difficulties in administrative planning and requires costly resource adjustments. From a
medical perspective, the lack of foresight results in delayed diagnoses, prolonged patient stays, increased costs
and strain on resources. The proposed solution disrupts the current traditional diagnostic process and provides
early insights into the trends of the public’s well-being. This enables governmental bodies, organizations, and
healthcare institutions to act pre-emptively and to manage their resources more effectively. The solution
provides a user-friendly environment to work in. A dynamic map that visually represents the risks associated
with the spread of diseases, providing an interactive and comprehensive view of the potential impact, while the
insights dashboard extracts and visualizes valuable insights, presenting risk levels and associated parameters in a
clear and comprehensive format.
Users and their needs
By synergizing AI diagnostic CDSS and the EO project 'AI Diagnostics for Health and Well-being through Earth
Observation Data in Europe,' users can benefit from the unique strengths of both components, enhancing their
achievements:
EO Diagnostics:
Health & Governmental Organizations:
Users: Health officials
Main Problem: Lack of a holistic diagnosis system with budget constraints
Gain: Addresses early disease detection needs, providing a comprehensive health indication solution for Europe
Clinical Decision Support System (CDSS):
Laboratories:
Users: Laboratory professionals
Main Problem: Late or incorrect diagnoses due to fragmented data
Gain: Facilitates cross-sectoral communication, ensuring correct and timely diagnoses, reducing costs
Clinics and Hospitals:
Users: Physicians and healthcare administrators
Main Problem: Reduced investment and slow processes
Gain: Accepted as part of research projects, streamlining processes, reducing bureaucratic efforts, and improving
patient treatment and diagnostics
Pharmaceutical Companies:
Users: Health data scientists
Main Problem: Handling big medical data for research
Gain: Offers automated mapping tools for standardization, making medical data usable for research and
development
Targeted Regions: Europe with a focus on DACH (Germany, Austria, Switzerland), Southern and Western
European nations, and Nordic states.
Service/ system concept
The User Interface/Dashboard ensures a user-friendly experience for inputting location and disease information.
It seamlessly presents predictions and suggestions, displaying relevant environmental factors impacting the
specified disease, and provides actionable recommendations based on the predictions. The User Input
Processing, powered by georaster processing packages, validates and processes user inputs from the dashboard,
meticulously verifying both location and disease details. In interaction with the Copernicus API, an open-source
tool with a completed connection, environmental data for the specified location are retrieved, querying for
factors like air quality, temperature, and humidity. The collected data is then processed for further analysis. The
medicalvalues Reasoning API, currently in a simulated prototype stage with the final version pending, utilizes the
medicalvalues knowledge graph to delve into the relationships between environmental factors and specified
diseases. It performs reasoning and inference based on the input disease, retrieving relevant information for
comprehensive analysis. The Prediction Engine combines environmental data from the Copernicus API with
disease-specific insights from the medicalvalues reasoning module. Applying machine learning or statistical
models, it generates predictions, determining the likelihood of various environmental factors on the specified
disease.
Space Added Value
UR-0100: The long-term data acquisition was achieved by connecting the platform to the Copernicus Sentinel
Open Access Hub, which provides access to the data collected, including the Sentinel 5P satellite, which is
relevant for this service. A data preprocessing pipeline was implemented in python to retrieve, aggregate, clean,
and combine the raw data for the analysis of the relevant parameters.
UR-0300: The Tropomi Instrument of the Sentinel 5P satellite possesses an adequate spatial resolution. In order
to ensure sufficient coverage for the entire area of interest, data from a period of six months was combined to
eliminate gaps caused by clouds or similar disruptions. The use of a geocoding API and the manual
implementation of formular for combining different coordinate systems enabled easy and intuitive targeted
examination of specific regions. Thus, users can take advantage of the high spatial resolution of the Tropomi
instrument, without the need for specialized expert knowledge.
Current Status
From April to September, the project progressed significantly, creating an abstraction overview, defining
technical requirements, and finalizing system architecture. Key milestones in August, including the Copernicus
API connection, data preprocessing pipeline, and parameter visualization, showcased a comprehensive approach
in medical diagnostics. In September, the focus shifted to medical evaluation and interface design for enhanced
usability. Moving forward, the project aims to target potential customers, establish B2B sales channels, and
refine its CDSS software based on user feedback. Simultaneously, it plans to develop partnerships in the
healthcare industry, conduct pilot programs, and ensure a skilled team and robust infrastructure. The focus also
includes customized marketing, attractive pricing, and optimized sales strategies, along with forming alliances
with industry associations and regulatory bodies.
