eHealth First Project Summary

eHealth First is an IT-platform to support decision-making in the field of health management, longevity, diagnostics, the prevention and treatment of common diseases for non-specialist users, medical specialists and researchers based on blockchain technology, machine learning, natural language analysis, neural networks, big data, clinical epidemiology, evidence-based medicine and telemedicine.

The project is developing and implementing an innovative IT platform for screening and optimal algorithms for maintaining health and diagnosing, treating and preventing various diseases and conditions. A project which is unique.

The platform will include a number of the most sensitive and specific, validated questionnaires with highest possible currently diagnostic effectiveness.

A range of the most sensitive diagnostic methods and the most effective medical interventions (taking into account the need to clarify the diagnosis and prescriptions of the attending physician), as well as most evidence-based lifestyle recommendations will be available on the basis of an innovative open medical knowledge platform in the field of aging and robust longevity. The open platform is being developed using A.I., such as Natural Language Processing methods for the ever-growing body of publications in medical science, machine learning, and neural networks. As a result, the IT platform will reduce the obsolescence of medical knowledge.

The open and free part of the platform will be an ontological network replenished using natural language and neural network processing methods semi-automatically (with expert pre-moderation) with the participation of both project staff and authorized qualified volunteers. The inference and visualization of search queries in a user-friendly intuitive interface based on the ontology project team has already created will greatly facilitate the search for scientific information, and the synthesis and acquisition of new scientific knowledge. This will be one of the first open systems for the deep processing of scientific medical texts and the first such system in the field of aging and longevity research in the world.

The IT platform includes two related software products.

The Personal Health Management Application (EHF Personal Health) is a web portal and mobile application with an integrated expert system that provides advisory services in a B2C format for non-specialist users, medical professionals, and potentially for other categories of users including experts and employers. The system involves the collection and storage of users’ personal data and will comply with the norms of the legislation in the field of personal data protection. It assumes mixed storage of data: centralized and decentralized in the blockchain.

The user interface provides for the registration of the user in the system, while collecting the master data (sex, age, etc.). There is also a system for electronic payment for services through electronic banking cards, mobile application stores (Apple Store, Google Market, etc.) and other methods of payment via the Internet (including own currency, ETH, BTC).

After registration, the user will be asked to undergo preliminary diagnostics screening. This structured questionnaire, compiled on the basis of the principles of evidence-based medicine, consists of questions that identify the basic indicators of health, collect information for categorizing this user within the system, collect estimates of biological age, a frailty index, and also give primary assessments of various body systems. For the preliminary diagnosis, the user does not need to undergo a survey using any laboratory-based methods. The user gives information about the results of previous medical tests and the questionnaire does not require any medical education. After passing the preliminary diagnostics, the system, using the algorithm developed in the course of the project, will formulate a list of the main recommendations for this user, and also offer additional diagnostics, including the use of specialized validated questionnaires, laboratory tests and medical consultations.

For each specialized diagnostic module, a separate algorithm will be developed that allows the user to clarify the danger of certain pathological conditions or diseases, and to give specific recommendations, including additional biochemical and other analyzes. Access to these modules is planned to be fee based. If the user has started working with the module but does not have the necessary tests to perform diagnostics within this module, they can return to this module later, after the necessary tests have been completed. The system saves the user information for each diagnostic module, and the user can continue to work with the system at any convenient time.

Within the framework of a personalized module, the user is provided with results in a user- friendly form, including assessments of the risk of various types of diseases, recommendations for lifestyle changes, educational information, including advice on the use of medication, scientifically based nutraceuticals and medical devices.

The algorithms of the system are to be constantly improved, updating them based on updated of the second module of the platform. Users will be able to get tested again in accessible modules and get the most up-to-date recommendations.

The application to support health decision-making, personal strategies for the diagnosis, prevention and treatment of diseases for non-specialist users and health professionals will include:

• an expert system for the primary diagnosis of the most common diseases and conditions on the basis of automated algorithms obtained on the basis of the principles of evidence-based medicine. Based on the tests, recommendations will be generated for laboratory tests and visits to medical specialists to clarify the preliminary diagnosis;
• the most up-to-date information on the diagnosis, prevention and treatment of diseases, therapeutic windows, contraindications, drug interactions, semi-automatically updated following new clinical guidelines, systematic reviews and meta-analyzes will be developed using NLP methods;
• indices of the biological age of a person;
• a frailty index;
• a general module for the primary prevention of age-related diseases;
• modules for people with chronic diseases (including those with metabolic syndromes, hypertension, ischemic heart disease, type 2 diabetes, etc.);
• special modules for patients with cancer, aimed at improving the quality of their lives.

The open IT platform for health professionals (EHF Biomed) will have the features of a database and analytical system in the field of biomedicine and related specialties. A key element of the application will be the constantly updated knowledge base on pathological aging processes and bio-medical anti-aging interventions. This knowledge base will be updated semi-automatically with the processing of an array of literature (including the Pubmed / MEDLINE platform), using natural language processing, machine learning and neural networks. This knowledge base, presented in the form of a scalable information system, will provide tools for searching and analyzing the most relevant scientific information on any biomedical issues in the field of longevity.

The application provides flexible possibilities for searching information, including using the resulting natural language processing graphs of the relationship between certain terms and text elements.

With the help of natural language processing, machine learning and neural networks in the medical databases, a search will be conducted for a series of keywords related to pathological aging processes, associated signal molecules, potential and approved diagnostic methods and medical interventions. An intuitive, user-friendly structure of the summary of scientific information will significantly reduce the time and improve the accuracy of scientific research.

It will have the most modern meta-analyses and systematic reviews of clinical trials (including Cochrane studies), studies of diagnostic methods, prevention and treatment of pathological aging processes and age-related diseases (indicating the level of evidence obtained on the recognized international scale), and at any given moment will provide access to the most relevant medical knowledge in the framework of biogerontology and age-related diseases.

Users will be able to create individual collections of materials, and subscribe to the appearance of new materials according to the formulated search criteria. Subscribers will receive regular lists of materials of interest through email and messengers. At the initial stage, the application provides an expert moderator, who will select the most suitable data, and standardize the presentation of these data to users. The technical feature of the second application is a search index created using the Sphynx Search system (or equivalent). The search index will allow you to quickly find any necessary information in a large database.

The system will be integrated with blockchain technology, including the development of a universal format for recording aggregated data from biomedical research.

See the Section “Key Technologies” in the White Paper and others for the details