HI HEALTH

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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.

This is illustrated by World Health Organization reports. Experts claim that there are many factors that affect the health of the world’s population: among them are environmental damage, increased stress levels, worsening of nutritional situation due to too much sugar, hormones and chemical components used in the product. Prophylaxis and prevention of illness in the future is a much cheaper and effective way to maintain health and prolong life, rather than cure disease. However, it is not always a predictable disease even if a person is continuously undergoing a medical examination, and most people know about an ex post facto disease attack. The lack of accurate predictions makes treatment more complicated and more expensive, and often even makes full recovery impossible. Result of,

The situation in this area can be substantially improved by a combination of drugs and artificial intelligence in a syncretic mixture. The modern selflearning system makes it possible to conduct a real-time comprehensive diagnosis of organisms with high accuracy, to identify previously unknown patterns between indicators of human organism activity and morbidity risk, to warn about the possible state of acute chronic illness. Implementing artificial intelligence will allow people to manage their health strategically. Because with credible knowledge about the risks a person will be able to take the necessary steps to prophylaxis the disease. That is precisely the mission to be met Hi Health.

What is Hi: Health?

Hi: Health is a global ecosystem analyst based on artificial intelligence. Personal ecosystem to diagnose the human body in real time.

Applying medical reports to a large number of patients, as well as indicators of health control tools, we teach artificial intelligence to ensure early diagnosis of different diseases and to determine unidentified causal relationships between organ function and body system and disease outbreaks. AI will be able to analyze a few deviations, which humans can not take note of, and also to get more accurate survey results (eg, electrocardiogram) generated from cleaning the device from noise. Also with Al’s help it would be possible to monitor the effectiveness of treating in real time and correct doctor prescription.

The problem is in the field of medicine

Only in the United States and the EU, hundreds of thousands of patients die every year because of a doctor’s diagnostic error. The economic costs associated with complications encountered in prescribed wrongful drugs are over $ 100 billion per year.

The main reasons for misdiagnosis are as follows:

Doctors specialize in certain organs or organism systems and often can not see the whole picture;
Lack of experience and physician problems in knowledge often lead to situations, when rare diseases can not be identified;
The lack of time that doctors have to analyze medical history, the reason is the high doctor’s workload (appointment with the patient) as well as the documentation takes a lot of time;
Complexity in the definition of disease according to X-ray, CT, MRI studies, histologic examination during non-standard types of disease, and also high dependence on subjective experience by an expert.
Based on the artificial intelligence of neural networks it will be possible to make a large number of differences in the field of medical diagnosis.

How does it work?

Platform options Opportunities for someone:

Downloading personal medical data
Safe and anonymous medical data storage
Appreciate in the form of getting tokens (tokens allow extending application functionality, buying health and life insurance)
Anonymous sales of your data for platform tokens
Analyze data using artificial intelligence to diagnose disease at an early stage
Purchase and connect tested devices (gadgets) for the diagnosis of organisms in an express manner
Make an appointment to undergo a medical examination
Seek and buy proven medications

Ability of artificial intelligence when using algorithms to analyze IR radiation

The AI algorithm analyzes the data obtained, based on the experience of thousands of physicians worldwide and millions of studies, determining the slightest correlation between changes in gadgets and human test results.
Identify patterns and sources of disease
Artificial Intelligence makes recommendations for lifestyle management based on the likelihood of disease occurrence
Create individual care and nutrition plans
Controlling the consumption of drugs
Keep track of the maintenance process

Tracker for Rocketbody real-time data collection

Body temperature
Rhythm of breath
Level of physical activity
Levels of alcohol in the blood
Levels of hemoglobin in the blood
Blood pressure
EKG
Heart rhythm

Ecosystem for doctors

Online consultation for patients
Sharing experiences with colleagues
Collaborative patient care
Monitor the truth of taking medication by the patient
Online controls the patient’s treatment process
Identify more accurate sources of disease with the help of AI
Access to neural networks for a fee.

Ecosystems for Business

The insurance company accepts a more accurate account of the possibility of an insured event. Increase their profits by minimizing the risk of paying insurance premiums. Selling health insurance through application
Pharmaceutical companies receive statistical reports on the sale of medicines, localized disease (urban) and the effects of drugs on a person. To personalize treatment, data can be obtained from a DNA database about a person’s predisposition to a particular disease according to his geographic residence.
Clinics improve methods of treatment and prevention of human diseases
Research centers and developers can use the benefits of data mining (detecting titles in the database) to get patterns. In today’s global competition, knowledge of the patterns found can provide additional benefits

What is the Mining Date?

Data Mining is the collective name for a combination of detecting technologies among previously unknown, non-trivial, interpretable data that are operationally useful and available from the knowledge needed to make decisions in different areas of human activity

Data Mining technology is a powerful tool of modern business analytics and data research to find hidden patterns and build approximate models. Data Mining is not based on speculation, but on real data.

Data mining tasks

Classification

The easiest and most common data mining tasks. In the result of completing the classification task, one can find indicators that characterize the group of objects of the studied dataset (class). According to this indicator a new object can be classified.

Methods for handling tasks

To complete a classification task one can use several methods including Nearest Neighbor, k-Nearest Neighbor, Bayesian Networks, induction of decision trees, neural networks.

clustering

Clustering is a logical follow-up to the idea of classification. This task is more complicated; the hallmark of grouping is that the object class is not predefined. The result of grouping divides objects into groups. Examples of methods for handling grouping tasks: “unattended learning”, special types of neural networks – self-governing maps of Kohonena.

Roadmap

July – September 2017 Studying problems in medicine and finding solutions for developing strategic maps

October-December 2017 Writing Whitepaper, developing smart contracts, creating architecture and developing prototype platforms, setting up marketing strategies.

January-April 2018 Run Pre-ICO, the pre-order RocketBody gadget, create a legal basis

May-August 2018 Launch of ICO, Issuance & HiHealth v1.0 with functions to collect (purchase) user data, partner programs with CIS clinics and laboratories,

August-January 2019 Buy medical data, process medical data, teach artificial intelligence, Buy medical data, process medical data, teach neural networks Predict the possibility of heart attack by analyzing multiple points of view (height, age, ECG / Echo reading, analysis, chronic morbidity) Diagnostic complaints common or disease based on blood chemistry symptoms and patients.

February-July 2019 Launch and publish HiHealth v2.0 with personal artly intelligent helper, broker launch date.

August 2019 Health and life insurance,

Tim

Aleksandr Potkin: CEO, CFO

Salman Qadir: International Business Manager

Egor Stepanichtchev: CIO

Konstantin Rerzhukou: SOFTWARE DEVELOPMENT

Eugene Makeychik: DISIGN

Michael Zhalevich: PENGEMBANGAN BLOKCHAIN

Eugene Koval: SOFTWARE DEVELOPMENT

Pavel Yeschenko: BLOKCHAIN DEVELOPMENT

Vladislav Vasilchyk: ANALISIS SISTEM