Health is one of the main factors affecting the quality of human life and the participation of its workforce. However, in recent years, the world’s situation on many diseases has worsened, including diabetes, cardiovascular disease, and more.Health is one of the main factors affecting the quality of human life and the participation of its workforce. However, in recent years, the world’s situation on many diseases has worsened, including diabetes, cardiovascular disease, and more.
Medical research in the past has attempted to create high levels of trust through peer review conducted by reputable medical journals such as the New England Journal of Medicine. Both methods of generating trust rely on a trusted central authority, either the government or a medical journal. As such, both methods are highly susceptible to fraud via corruption or innocent errors of the centralized authority. This has led to widespread distrust in medical research. Bitcoin operates differently, because it sets up a method of relying on a distributed network based upon a mathematical algorithm, rather than centralized authority susceptible to human error.
Hi:Health is a global ecosystem analyst based on artificial intelligence. The personal ecosystem for diagnosing a human body in real time.
Applying medical reports of great amount of patients, and also indicators of health-control gadgets, we teach artificial intelligence to ensure early diagnosis of different illnesses and determine previously unidentified cause-and-effect relationship between functioning of body organs and systems of the body and outbreak of diseases. AI will be able to analyze slightest deviations, which human can’t notice, and also to get more accurate survey results (for example, electrocardiogram) resulting from clearing devices of noise. Also with the help of Al it would be possible to monitor effectiveness of treating in real time and correct doctor’s prescriptions.
The problem in the field of medicine
Just in USA and EU hundreds of thousands of patients die annually due to doctors’ misdiagnoses. The economic cost connected with complications that encountered in wrong prescription of drugs is more than $100 billion per year.
The main reasons of misdiagnoses are as follows:
The doctors are specialized in certain organs or organism’s system and often can’t see the overall picture;
Lack of experience and doctors’ problems in knowledge often lead to situation, when rare diseases can be not identified;
Lack of time that doctor has for analyzing medical history, the reason is doctor’s high workload (appointments with patients) and also documentation takes significant amounts of time;
The complexity in the definition of the disease according to X-ray, CT, MRI studies, histological examination during nonstandard kind of disease, and also high dependence on subjective experience by an expert.
Based on neural networks artificial intelligence will allow to make a huge amount of difference in the field of medical diagnosis.
How it works?
Opportunities Options of the platform for a person:
Downloading personal medical data
Secure and anonymous storage of medical data
Rewarding in the form of getting tokens (tokens allow extending the application functionality, purchasing health and life insurance)
Anonymous sales of your data for platform tokens
Analysing data using artificial intelligence for diagnosing diseases at early stages
Purchasing and connecting tested devices (gadgets) for express diagnosing of the organism
Making appointments for undergoing medical examination
Searching and purchasing proven drugs
The ability of artificial intelligence when using algorithms to analyze IR radiation
AI algorithms analyse the data obtained, based on the experience of thousands of doctors around the world and millions of studies, determining the slightest correlation between the changes in gadgets and the results of human tests.
Identifies the patterns and sources of a disease
Artificial Intelligence makes recommendations for lifestyle management based on the possibility of disease occurrence
Creates an individual treatment and nutrition plan
Controls the consumption of medications
Tracking the treatment process
Tracker for real-time data collection Rocketbody
Rhythm of breath
Physical activity level
Blood alcohol level
The level of hemoglobin in the blood
Ecosystem for a doctor
Online consultations of the patients
Sharing of experience with colleagues
Collaborative patients’ treatment
Monitoring the correctness of taking medication by patients
Online controlling the process of patients’ treatment
Identifying the more accurate source of the disease with the help of AI
Access to neural networks on a fee basis.
The Ecosystem for Business
Insurance companies receive a more accurate calculation of the probability of occurrence of an insured event. Increase their profits by minimizing the risks of paying insurance premiums. Selling health insurance through applications
Pharmaceutical companies receive statistical reports on the sales of medicines, typical regional (urban) diseases and the effects of medicines on a person. In order to personalize the treatment, the data can be obtained from the DNA database about the predisposition of a person to certain diseases according to his/her geographical residence
Clinics improve the methods of treatment and prevention of human diseases
Research centers and developers can use the benefits of data mining (the detection of titles in databases) in order to obtain patterns. In the current global competition, the knowledge of the discovered patterns can give additional advantage.
Information mining undertakings
The least demanding and most regular Data mining errand. In the aftereffect of finishing the undertaking of order, one can find pointers that describe gatherings of objects of researched dataset (classes). As indicated by these markers the new question can be characterized.
The techniques for managing the undertaking
With a specific end goal to finish the undertaking of characterization one can utilize a few strategies including Nearest Neighbor, k-Nearest Neighbor, Bayesian Networks, acceptance of choice tree, neural systems.
Grouping is the consistent follow-up to the possibility of order. This errand is more muddled; the trademark highlight of grouping is that classes of articles are not foreordained at first. The aftereffect of bunching is separating objects into gatherings. A case of technique for managing the errand of grouping: “unsupervised taking in”, an extraordinary sort of neural systems – self-arranging map Kohonena.
July – September 2017 Studying issues in medication and discovering answers for build up a vital guide
October-December 2017 Writing Whitepaper, developing a smart contract, creating an architecture and developing a prototype platform, preparing marketing strategy.
January-April 2018 Run Pre-ICO, pre-order gadget RocketBody, create legal base
May-August 2018 Launching the ICO, publishing &HiHealth v1.0 with the functionality to collect (purchase) user data, partner programs with clinics and CIS laboratories,
August-January 2019 Buying medical data, processing medical data, teaching artificial intelligence, Buying medical data, processing medical data, teaching neural networks Prediction of possible heart attack by analyzing variety of viewpoints (height, age, EKG/Echo readings, analyses, chronic morbidity) Diagnostics of common complaints or diseases based on blood chemistry and patient symptoms.
February-July 2019 Release and publish HiHealth v2.0 with a personal artificially intelligent helper, launch broker’s date.
August 2019 Health and life Insurance.
Aleksandr Potkin: CEO, CFO
Salman Qadir: International Business Manager
Egor Stepanichtchev: CIO
Konstantin Rerzhukou: SOFTWARE DEVELOPMENT
Eugene Makeychik: DESIGN
Michael Zhalevich: BLOCKCHAIN DEVELOPMENT
Eugene Koval: SOFTWARE DEVELOPMENT
Pavel Yeschenko: BLOCKCHAIN DEVELOPMENT
Vladislav Vasilchyk: SYSTEM ANALYST
Aliaksey Mkrtychan: DATA SCIENCE DEVELOPMENT
Volha Hedranovich: MSC DATA SCIENTIST
Andrei Lapanik: DATA SCIENCE SYSTEM ARCHITECT
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