Obtaining data of different types in one period of time helps to more accurately describe the state of human health at the moment
Challenges in health
data storage.
data storage.
Lack
of Data
of Data
- Misdiagnosis
- Lack of preventive healthcare
- Lack of application
Oversaturation
with Data
with Data
- What matters among the noise?
Data Ownership & Transparency
- You own your data
- Trust in Data / Validation
- Use of analytics
Smart life data escrow
Data
users
users
Use live search to compile cus- tom datasets based on unique search criteria. They access phenotypic and other ano- nymized data, having user consent, to accelerate research and drug development in a traceable way.
Ai-based data
verifier
verifier
Proprietary and flexible sys- tem for data validation and scoring in order to classify and evaluate uploaded data for better future analytics.
Data
aggregators
aggregators
Institutions and individu-
als (healthcare organizations, doctors,etc.) use the platform for data storage and analytics.
als (healthcare organizations, doctors,etc.) use the platform for data storage and analytics.
Data
owners
owners
Individuals/Patients, who con- tribute or otherwise upload their data.
Data type
System described —
key metrics
key metrics
Security
and data privacy
and data privacy
Secured data storage, allowing convenient mechanisms for data encryption and storage, minimizing the risks of data leaks. Selected unique security features include data encryp- tion algorithms, key splitting, and advanced deployment.
Multiple data types
in one ecosystem
in one ecosystem
Longenesis helps to organize various data types from a patient/group of patient, allow- ing to query data by a variety of phenotypic types and forming a "data lake" for future ana- lytics and aggregation.
Data
analytics
analytics
The ability to analyze collected data types and correlate them in order to "view the bigger picture", meaning in-depth health analytics for certain patient/cohort of patients.
Full data
access control
access control
Ability to manage the access controls to cer- tain data.
Data
validation
validation
Automatized system for data validation and scoring in order to classify and evaluate up- loaded data for better future analytics.
Data
traceability
traceability
Gives the users an opportunity to see who and when accessed their data.