Batu Permata: Hi:Health

Date Broker of Personal Medical Data

Health is one of main factors that influence the quality of human’s life and his labour force participation. However, in recent years, the world situation concerning many diseases is worsening, including diabetes, cardiovascular disease and lots more.

This is illustrated by the reports of the World Health Organization. The experts claim that there is a multitude of factors that impact the health of the world’s inhabitants: among them is deterioration of the environment, increased levels of stress, worsening nutrition situation because of too much sugar, hormones and chemical components used in products. Prophylaxis and preventing future illnesses is much more cheaper and effective way of keeping good health and prolonging life, than treatment of disease. However, not always illnesses can be predicted even if one constantly undergoes a medical examination, and most of people get to know about the onslaught of diseases ex post facto. Lack of accurate predictions makes treatment more complicated and more expensive, and even often makes full recovery impossible. As a result, people lose an enormous amount of money on medication with an aim just to keep living, not to mention recovery.

Situation in this field can be fundamentally improved by combination medicine and artificial intelligence in a syncretic mix. Modern selflearning systems allow to conduct a real-time comprehensive diagnosis of organism with high accuracy, to identify previously unknown patterns between indicators of activity of human organism and risks of morbidity, to warn about possible acute state of chronic diseases. Applying artificial intelligence would allow people to manage their health strategically. Because with trustworthy knowledge about risks one will be able to take the necessary measures to prophylaxis of illnesses. That is precisely the mission which Hi Health is required to accomplish.

What is Hi:Health?

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

Body temperature
Rhythm of breath
Physical activity level
Blood alcohol level
The level of hemoglobin in the blood
Blood pressure
ECG
Heart rhythm

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

What Date Mining is?

Data Mining is a collective name for combination of technologies that detect among the data previously unknown, non-trivial, operationally useful and available interpretations of the knowledge required for making decisions in various spheres of human activity

Data Mining technologies are a powerful apparatus of modern business analytics and a data research for finding hidden patterns and building forecast models. Data Mining is based not on speculation, but on real data.

Data mining tasks

The classification

The easiest and most common Data mining task. In the result of completing the task of classification, one can discover indicators that characterize groups of objects of investigated dataset (classes). According to these indicators the new object can be classified.

The methods for dealing with the task

In order to complete the task of classification one can use some methods including Nearest Neighbor, k-Nearest Neighbor, Bayesian Networks, induction of decision tree, neural networks.

Clustering

Clustering is the logical follow-up to the idea of classification. This task is more complicated; the characteristic feature of clustering is that classes of objects are not predetermined initially. The result of clustering is dividing objects into groups. An example of method for dealing with the task of clustering: “unsupervised learning”, a special kind of neural networks – self-organizing map Kohonena.

Roadmap

July – September 2017 Studying problems in medicine and finding solutions to develop a strategic map

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,

Team

Aleksandr Potkin: CEO, CFO

Salman Qadir: International Business Manager

Egor Stepanichtchev: CIO

Konstantin Rerzhukou: SOFTWARE DEVELOPMENT

Eugene Makeychik: DISIGN

Michael Zhalevich: BLOCKCHAIN DEVELOPMENT

Eugene Koval: SOFTWARE DEVELOPMENT

Pavel Yeschenko: BLOCKCHAIN DEVELOPMENT

Vladislav Vasilchyk: SYSTEM ANALYST