WO2022130006A1

WO2022130006A1 - A prognosis and early diagnosis method and system and choosing the best treatment based on data fusion and information analysis by artificial intelligence, with the ability to modify and improve information and results according to machine learning

Info

Publication number: WO2022130006A1
Application number: PCT/IB2020/062255
Authority: WO
Inventors: Soroush SARABI; Ali SOLTANMORADI; Ameneh SHADLO; Hanieh TAVASSOLI; Raya MOHSENIAN; Mahsa ZAMANI
Original assignee: Sarabi Soroush; Soltanmoradi Ali; Shadlo Ameneh; Tavassoli Hanieh; Mohsenian Raya
Priority date: 2020-12-19
Filing date: 2020-12-19
Publication date: 2022-06-23

Abstract

The invention of diagnosis and early prognosis method and system and choosing the best treatment based on data fusion and information analysis by artificial intelligence, with the ability to modify and improve information and results according to machine learning is a method and mechanism for early prognosis,diagnosis and treatment of diseases, which includes a computer with the ability to process information with high volume and speed as a central server or a small microchip to convert and match the input information by pre-designed compilers.The server connected to the target community's data base manually or online can enter the information related to the previous generations as well as the date of birth and death of individuals. According to the artificial intelligence analyzer system and the changes made in the estimation and diagnosis databases and algorithms,this invention can submit message through IoT devices.

Description

A PROGNOSIS AND EARLY DIAGNOSIS METHOD AND SYSTEM AND CHOOSING THE BEST TREATMENT BASED ON DATA FUSION AND INFORMATION ANALYSIS BY ARTIFICIAL INTELLIGENCE. WITH THE ABILITY TO MODIFY AND IMPROVE INFORMATION AND RESULTS ACCORDING TO MACHINE LEARNING

TECHNICAL FIELD OF THE INVENTION

The present invention relates to an intelligent system and also a prognosis and diagnosis method for disease. Also this invention relates to the data fusion and analysis according to extracted information as well as machine learning and deep learning systems.

PRIOR ART

With improving the medical science and accurate prognosis method comprising various radiographies, diagnostic systems based on chemical tests, extracted results in pathology and also the information obtained based on human analysis and machine analysis, accurate diagnosis of diseases and treatment methods are constantly evolving and improving. In this regard, the use of diagnostic tools, methods and devices as the first step in the diagnosis and treatment process, has been institutionalized and generalized by physicians. However, since the study of reasoning and diagnosis of disease by human can include small and large human errors, so every year, a large number of patients enter to more advanced stages of disease due to lack of well-timed diagnosis or errors occur in the diagnosis process which is sometimes an irreversible stage and causes permanent problems and in some cases the patient to die. Therefore, the use of data analysis methods based on predefined algorithms with the help of computers and other analyzer machines has reduced errors and potential problems. In this regard, many people have designed methods, programming systems and have used the computer processors. Among the cases, we can mention the technologies presented in each of the following patents:

An invention with EP3108393A1 patent number which is filed on 19/02/2014 in EPO named “Disease prediction system using open source data” is a disease prediction system using open source data. The system includes a preprocessing module, a learning module, and a prediction module. The preprocessing module receives a dataset of N trend results related to a disease event and generates an enhanced filter signal (EFS) curve related to the disease event. The learning module receives the EFS curve and generates a predicted number of cases of the disease e vent and, using a plurality of machine learning methods, generates a plurality of predictions that the disease event will happen within a future time period. The prediction module determines precision and recall for each of the plurality of predictions and, based on the precision and recall, provides a likelihood that the disease event will occur.

Another invention with W02002047007A2 publication number which is filed on 07/12/2000 in WIPO, named “Expert system for classification and prediction of genetic diseases” is a system for classifying genetic conditions, diseases, tumors etc., and/or for predicting genetic diseases, and/or for associating molecular genetic parameters with clinical parameters and/or for identifying tumors by gene expression profiles etc. The invention specifies such methods, devices and systems with the steps of providing molecular genetic data and/or clinical data, automatically classification, prediction, association and/or identification data by means of a supervising machine learning system. Thus, information obtained by new techniques like cDNA microarrays that are profiling gene expression in tissues might be beneficial for this dilemma. This invention is also directed to a computer program comprising program code means for performing the method of any one of the preceding embodiments when the program is run on a computer. Further preferably, the computer program product comprises program code means stored on a computer readable medium for performing the above mentioned method when said program product is run on a computer.

In another invention with US20150141826A1 publication number which is granted on 25/06/2019 in USPTO, named “Prediction of diseases based on analysis of medical exam and/or test workflow” is a system for prediction of disease based on analysis of medical exam and/or test workflow. There is a method, computer program product and/or system which performs the following actions (not necessarily in the following order): (i) receiving a first medical workflow obtained from a plurality of medical acts performed in sequence that related to care of a patient; and (ii) applying a set of condition-indication rules to the first medical workflow to determine first condition information which relates to a likelihood that a first medical condition exists in the patient. The receiving and applying steps are both performed by a machine that is controlled by machine logic.

In another invention with W02004015608A2 publication number which is filed on 02/08/2002 in WIPO, named “An expert system for clinical outcome prediction”, is an expert system for clinical outcome prediction which in particular, the invention relates to a generic data-mining system for predicting the development of a disease and/or for identifying high-risk patients. A method for predicting the development of a disease and/or identifying high-risk patients, and a system for performing the method, is provided, including the steps of providing molecular genetic data and/or clinical data, pre-processing the data, selecting a predetermined number of variables out of the provided data according to their combined/mutual information content, automatically generating prediction data by means of machine learning.

An invention with US8504343B2 patent number which is granted on 06/08/2013 in USPTO, named “Disease diagnoses-bases disease prediction” is a system for predicting future disease for a subject comprising: a population information set comprising population disease diagnoses for members of a population; a subjectspecific information set comprising at least one subject- specific disease diagnosis; and a diagnoses-based prediction module configured to predict one or more future diseases for the subject based on said subject- specific disease diagnosis and said population disease diagnoses for population members having at least one disease in common with the subject. More specifically, different prediction models may be utilized to generate the disease predictions, individually or simultaneously. The generated disease predictions may be ranked, filtered or otherwise modified to provide it in a form that is useful to the operator. As used herein, “diagnosis” refers to the identification or recognition of a disease or medical condition by the signs and symptoms gathered from, for example, interviewing, laboratory testing, and examining a subject.

Another invention with US20160073969A1 publication number which is filed on 15/09/2014 in USPTO, named “Medical Imaging System Providing Disease Prognosis” is a medical imaging system that processes input data (imaging and/or non imaging) having high dimensionality and few samples to learn from, by using multiple ranks of machine learning modules each dealing with a separate portion of the clinical data. The outputs of the individual machine learning modules are the combined to provide a result reflective of the complete image data set. The present inventors have developed a medical imaging system that provides a machine learning architecture that can learn from clinical data with high dimensionality but a low number of samples incident to a small clinical study. Generally, the system divides up the data (splits the high dimensional data into multiple sets of smaller dimensions) for independent training of different “smaller” machine learning modules so that significant input data will be exposed and emphasized during the training, without forcing the system to be lost in the high dimensionality of the data. Once exposed and emphasized, the outputs of multiple such smaller machine learning modules are combined, for example, by a second machine learning module, to provide an overall result.

In an invention with US8296247B2 patent number which is granted on 23/10/2012 in USPTO, named “Combination machine learning algorithms for computer-aided detection, review and diagnosis” is a method of reviewing medical images and clinical data to generate a diagnosis or treatment decision is provided. The method includes receiving, at a computer-aided detection (CAD) system, the medical images and clinical data, processing the medical images and clinical data; to generate initial finding candidates and clustering the initial finding candidates into a plurality of groups. The method further includes classifying the initial finding candidates using machine learning algorithms integrated into the CAD system into one or more categories one or more categories of the initial finding candidates using type 2 fuzz logic, and determining detection and assessment statistics based on at least the assessed categories and classified findings using Bayesian probability analysis. The method also includes modifying the classified findings and assessed categories based on additional interactive input, and generating the diagnosis or treatment decision based on the determined detection, assessment statistics, and the additional interactive input.

In the invention with AU2013351947A1 patent number which is granted on 02/12/2013 in Australian Patent Office, is a method used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response. The method of this invention comprising the steps of: (a) obtaining a blood sample from a subject; (b) cleaving proteins in said blood sample to provide a sample comprising peptides; (c) analyzing said sample for the presence of at least ten peptides; (d) comparing the results of analyzing said sample with control reference values to determine a positive or negative score for the presence of an adenoma or polyp of the colon. Also this invention recommends a treating method which is removal of adenoma or polyp tissue. The method of this invention can detect no symptoms for colorectal carcinoma, no family history for colorectal carcinoma, and no recognized risk factors for colorectal carcinoma other than age.

In another invention with US20180096742A1 publication number which is filed on 22/01/2017 in USPTO, named “Systems and methods for treating, diagnosing and predicting the occurrence of a medical condition” use clinical information, molecular information and/or computer-generated morphometric information for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67 -positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area.

The other invention with EP3534372A2 patent number which is filed on 04/08/2014 in EPO, named “Systems and methods to predict the progression of disease involving lesions in blood vessels” systems and methods are disclosed for predicting the progression of disease from factors like vessel geometry, physiology, and hemodynamics, said progression in disease comprising the onset or change over time of lesions in a blood vessel of a patient. One method includes: training a machine learning system based on longitudinal data of a plurality of individuals, that is corresponding data taken from the same individuals at different points in time, of vessel geometry, physiology, and hemodynamics, the data used to train the machine learning algorithm comprising multiple time-variant scans of the same individual taken at different times, to learn vessel characteristics in a location at an earlier time point that are correlated with the progression of disease in the same location at a later time point; acquiring an image of a patient; and for imaged locations in the patient, using the machine learning system's training data of local disease progression to predict the change in disease at said locations.

Up to now, despite all medical research focused on deciphering the causes and mechanisms of a specific disease, the development of an accurate and fast diagnosis method is still a challenging issue in therapeutic aims. Traditional methods of diagnosis are rapidly getting out of the way, and instead, techniques able to speedily and efficiently produce high amounts of data are substituted. Methods with the capability of data-mining and the hierarchical manner in decision-making should also be employed to obtain definite results from big data in medical aims.

The term “omics” refers to an increasing number of disciplines with the “omics” suffix, including Genomics, Epigenomics, Transcriptomics, proteomics, metabolomics, and Lipidomics, and glycomics. Omics aims to monitor the behavior of so many biological variables at once. Omics tends to accomplish a comprehensive characterization and quantification of so many biological molecules to study the structure and fundamentals of an organic function at different levels. To clarify the subject, omics technology is employed to unveiling the secrets of biological causes and mechanisms of a particular disease for future accurate diagnosis and prognosis.

Employing multiple-omics technology creates profound advantages over just using a single-omic analysis. Most of the prevalent diseases are multifactorial. Analyzing the causes of them by only a single-omic technology and analyzing a specific factor confine the comprehensive and accurate diagnosis and therapeutic. Studying just a single factor in a multifactorial disease may also result in implying defective and false causations. Multi-omics technology generates detailed information about different aspects of sicknesses. The idea of utilizing different omics provides the possibility of discovering the etiology of the most prevalent diseases caused by multiple factors such as certain types of cancers, obesity, and Alzheimer's. This approach also provides the capability of thoroughly understanding the relations between different factors and their impact on one another. Omics allows the study of associated multifactorial causes of disease by gathering data from different aspects, such as data on gene expression, cellular metabolism, and so on.

Despite all the privileges that the multi-omics technology provides, it still faces some substantial issues. The complexity of the etiology of diseases is the first challenging problem. Analyzing data obtained through omics technology is a time consuming and complex process because the expert confronts with large volume of data and also generating data on different aspects of the sickness is a timeconsuming procedure, which sometimes it is not possible to meet the deadline. To explain the point, the results will be provided when the disease would have made significant progress, and hence the treatment is not possible anymore, or the patient would have died. Also, the factors can undergo significant evolutions over time or fluctuate by environmental parameters and lifestyle habits. Most of the clinical experiments may present false positive or false negative results due to the nature of the intervention of human resources in diagnostics or the errors that occurred because of the experimental procedures. Not only in size and random-collection of the sample which confines the accuracy of the results, but also with this pool of data, noise detection is another issue. In fact, the optimization of diagnosis method such as the sample size or choosing the sample from a specific section is among challenges of traditional diagnosis.

The necessity to a hierarchy analyst system and a system with the ability for the fusion of related data and deduction of results and also speaking about large amounts of data brings the idea of employing artificial intelligence to the mind. To efficiently use all this data generate by omics technology, machine learning, and deep learning methods should be utilized. Due to the changing and progressing nature of a disease, the fluctuations and changes should be recorded over time. loT devices and all available sensors in the market for assessing the body function can provide the possibility of recording every change or progress in different eras of omics. Dozens of smart objects should be utilized to monitor the suspected case at every moment in different environmental parameters and various lifestyle habits such as food habits to investigate the impact of circumstances in disease progress and therapeutic. The data obtained by these devices including heart beat, blood glucose level, blood pressure and another data which are recorded through these devices, apply as up to date data by which the system is able to make decision for the patient at the moment, then ML and DL should be employed for decisionmaking, and diagnostic techniques-optimizing, and also noise eliminating and finally relate this whole data to generate a comprehensive and accurate result about the existence of the disease, the causes of it, and the best way to cure it. Also, this data should be saved in an information bank for future decisions in patient’s therapeutics or to utilize for the study of the probability of transferring this disease to the next generations and predicting and preventing it. By this smart decisionmaking procedures in hand, the results are provided, and also multiple factors and the impact of them on each other are determined, and the influence of different non-genetic parameters is obtained. To inform the doctor team and the patient about the results, loT devices are employed to send notifications and messages.

EXISTED PROBLEMS IN PRIOR ARTS

Among the problems in the structure of the mentioned technologies, we can mention the discrete effect of each method’s data on decision making in other methods. Since the human body and other living things are in fact an integrated mechanism, changes in any organ of the body can be consider to have direct or indirect effects on other parts of the body. Generally, in each of the available technologies, the process of examining the elements and factors of the disease accomplish lonely by a single mechanism, or the analysis of the mentioned information as primary information is done by artificial intelligence or other analytical methods. Now it should be noted that generally the patient enters the stage of diagnosis and treatment process when the disease has manifested itself widely, and therefore, despite the diagnosis, we have lost a good opportunity for treatment and, consequently, have to deal with a more advanced level of the disease and proceed to treat it. Separation of information related to different methods can in some cases lead to errors and the error also weakens the patient's chances of treatment or shortening the treatment time.

DESCRIPTION OF THE INVENTION

The present invention is a method and mechanism for early prognosis, diagnosis and treatment of diseases, which includes a computer with the ability to process information with high volume and speed as a central server or a small microchip without the need for a PC. On the computer, it will be possible to convert and match the input information by pre-designed compilers. The server connected to the target community’s data base manually or online can enter the information related to the previous generations as well as the date of birth and death of individuals. Besides, the connection of the central computer with the database related to the medical information of each parent and, of course, the previous generations will be available manually or online.

Also, the access of central computer to a software that can track people's daily habits, including diet, physiological information, daily ambulation and physical trainings, the place where people live or their daily traveling, environmental pollution, including pollution of water, air, noise, food or microbial and radioactive pollutions are also available. Also, the access of central computer software to the medical information of the individual is online with the ability to analyze images and test results. Now, by entering a new person into the system of present invention, for example a newborn baby, the genetic map of person, based on the analysis of the person's DNA, is initially considered as the basis for identification. According to the genetic map, after analyzing the individual's genome, first a result and then the initial analysis of the effects of each gene on the individual's physical condition is created. Therefore, according to the history of events, genome, data obtained through all omics technologies like transcrip tomics, life time and physiological characteristics of parents and ancestors, in the next step, a new edition on the results and probabilities of current or future diseases will be presented by an artificial intelligence analyst. The location of the individual, weather conditions and the usual diet of the subject as factors affecting the physical condition of the person at the said stage will affect the results and predictions made. In the next step, the results of the analysis are performed using information related to the place of residence and work, such as environmental pollution or the effects of environmental substances on the physiology of the person's body. The existence of test results and circumstances occur in the scope of individual’s health, can be a model to modify the prediction and estimation algorithm in future. The fusion of said information with medical examining results comprising test results, all clinical data like radiology images, blood sample test result and biopsy, the information obtained from systems related to diagnosis and other medical information of individual, analyze and monitor in an intelligent manner and also diagnose by entering new data, through artificial intelligence mechanism. The structure of artificial intelligence always maintains a chain of related elements to an individual which has significant interaction as analytical results of individual’s health and patient’s situation. Now by comparing the chain of each person’s data as well as results obtained through modification of information and estimated final results and actual final results which are available in others structures, the artificial intelligence system can create a significant algorithm among individual’s habits, genetic map, diet and all related information to the individual and these created algorithms in each part of knowledge of health can provide a correct source for disease prognosis with high accuracy. Now, according to the artificial intelligence analyzer system and the changes made in the estimation and diagnosis databases and algorithms, the structure of the present invention can submit message through loT devices as well as personalizing the manner of treatment, send advice in a personalized way for each person, estimating and monitoring online health conditions for each subjects of the server. Following, considering the possibility of the process of comparing the results obtained from each diagnostic method with the same results in the other persons, it is possible that in a very large range of human colonies with the correct separation of categories such as color, race, physiological factors and personal elements of individuals, identify factors related to a healthy person and also described each of the diseases and its side effects on various organs of an individual as well as other individuals in a colony and community with a significant interpretation of the condition of the individual(s). In this section, the mentioned information is analyzed by artificial intelligence and the results will be a kind of creation of new and correct knowledge based on digits and statistical numbers. Now, if there is side effect or suspicion for the existence of the disease, according to the protocols approved by the medical community take tests or samples, and convert the results of each test into processable information on the main server of this place which these results assess by artificial intelligence in the form of numerical analysis or based on image processing according to modified machine algorithms and according to high accuracy in reviewing information and clarity and separation of images for artificial intelligence, results obtained from fusion of each individual’s data with the new results, can provide the most accurate diagnosis of the disease for the therapeutic physician. For example, if the tissue of the intended person examine through pathology process, the correct analysis of the available elements in the online and on time extracted images from microscopes and other diagnosis equipments accompanying with chemical information obtained from the tests performed on the tissue as well as the results obtained from the laboratory devices considering the history and the estimated results from condition fusion of patient's previous data with the results of similar people as well as similar images of the discussed tissues in the field of pathology can initially define the exact requirements of each person's tissue examination in a customized and personalized manner for the same person, i.e. in discussion about the diagnosis for each person, while considering all the previous aspects and the written diagnostic protocols in a completely specialized way, special cases about the person are examined and cause a more accurate diagnosis of the disease. Also, due to the use of results obtained from the studies of a large number of people with each other and considering the obtained evidences and results, it is possible to diagnose more accurate. In the next step, while presenting the correct treatment protocols, by entering the correct treatment methods applied on each individual, the progress of treatment and also the final results of the treatment method can be done by examining the colony of similar patients and treatment methods, which can provide the best method of treatment with the suitable limitations as the optimal treatment method to the physician and in case of need for surgery, a surgical process can be simulated based on the available data from the patient's body, genetic conditions, physiological elements, similar surgeries, as well as the diagnosis made on the patient with the help of artificial intelligence, and suggest the mentioned process as the surgery’s model to the physician considering various facilities and different methods. The possibility of presenting the media of the process can clarify the course of treatment and the process of future recovery before starting the treatment process. In this invention, actually an inventive step takes regarding to integral analysis of existed diseases in a colony or a community by fusion of each individual’s data and creating previous information chain system and also comparing the similar elements of the chains and also the possibility to predict the epidemics and similar disease in colony increase and the chance to predict the disease and in particular reducing errors in diagnosis assume as different steps here.

DESCRIPTION OF DRAWINGS

Figure 1 which shows the schematic image of the manner of operation of present invention comprising below mentioned parts:

1. Individual’ s data

2. Genetic data

3. Therapeutic information

4. Information about parents

5. Previous disease

6. Current disease

7. Tests results

8. CT scan and MRI results

9. CBC results

10. Data about disease

11.How to deal with disease?

1 . Therapeutic methods

13. When afflict the disease?

14. Analysis

15. Diagnosis of epidemic disease

16. Surgical methods

Claims

What is claimed is:

1. The invention of diagnosis and early prognosis method and system and choosing the best treatment based on data fusion and information analysis by artificial intelligence, with the ability to modify and improve information and results according to machine learning comprising at least a central computer and at least a data transfer network and at least an information entry port and at least a compiler to convert the image data to the binary data and at least a system for collecting medical information of people and at least a database from history of people’s disease and their treatment and at least a data analyzer software and at least a database of known disease and its symptoms, affects and treatment methods and the results thereof and at least a database from history of disease and its treatment method related to patient’ s parents and ancestors and at least an analyzer structure of artificial intelligence and at least a machine learning system and at least a database from results of tests, radiography, ultrasonography, CT scan, MRI or any other data from common diagnostic methods and also a database from genetic map of people to analyze available elements, predict the procedure of creation and development of disease and also choosing the best treatment method.

2. The invention of claim one in which a computer with the ability to process information with high volume and speed as a central server is able to convert and match the input information by pre-designed compilers.

3. The invention of claim one in which the central server is connected to the target community’s data base and manually or online can enter the information related to the previous generations as well as the date of birth and death of individuals. The invention of claim one in which the connection of the central computer with the database related to the medical information of each parent and, of course, the previous generations will be available manually or online. The invention of claim one which the central computer is connected to a software that can track people's daily habits, including diet, physiological information, daily ambulation and physical trainings, the place where people live or their daily traveling, environmental pollution, including pollution of water, air, noise, food or microbial and radioactive pollutions. The invention of claim one which the access of central computer software to the medical information of the individual is online with the ability to analyze images and test results. The invention of claim one which by entering a new person into the system of present invention, for example a newborn baby, the genetic map of person, based on the analysis of the person's DNA, is initially considered as the basis for identification. The invention of claim one which according to the genetic map, after analyzing the individual's genome, first a result and then the initial analysis of the effects of each gene on the individual's physical condition is created. The invention of claim one which according to the history of events, genome, data obtained through all omics technologies like transcriptomics, life time and physiological characteristics of parents and ancestors, in the next step, a new edition on the results and probabilities of current or future diseases will be presented by an artificial intelligence analyst. The invention of claim one which the location of the individual, weather conditions and the usual diet of the subject as factors affecting the physical condition of the person at the said stage will affect the results and predictions made. The invention of claim one in which the results of the analysis are performed using information related to the place of residence and work, such as environmental pollution or the effects of environmental substances on the physiology of the person's body and required modifications on predicted results. The invention of claim one which the existence of test results and circumstances occur in the scope of individual’s health, can be a model to modify the prediction and estimation algorithm in future. The invention of claim one which the fusion of said information with medical examining results comprising test results, all clinical data like radiology images, blood sample test result and biopsy, the information obtained from systems related to diagnosis and other medical information of individual, analyze and monitor in an intelligent manner and also diagnose by entering new data, through artificial intelligence mechanism. The invention of claim one which the structure of artificial intelligence always assesses a chain of related elements to an individual which has significant interaction as initial information to obtain analytical results of individual’s health and patient’s situation. The invention of claim one in which by comparing the chain of each person’s data as well as results obtained through modification of information and estimated final results and actual final results which are available in others structures, the artificial intelligence system can create a significant algorithm among individual’s habits, genetic map, diet and all related information to the individual and these created algorithms in each part of knowledge of health can provide a correct source for disease prognosis with high accuracy.

16. The invention of claim one which by artificial intelligence analyzer system and checking the changes made in the estimation and diagnosis databases and algorithms, this invention can submit message and activate loT devices to announce or modify the situation or to control it.

17. The invention of claim one in which can simultaneously monitor and track the personalized manner of treatment, sending advice in a personalized way for each person, estimating and monitoring online health conditions for each subjects of the server.

18. The invention of claim one which regarding to the possibility of process of comparing the results obtained from each diagnostic method with the same results in the other persons, it is possible that in a very large range of human colonies with the correct separation of categories such as color, race, physiological factors and personal elements of individuals, identify factors related to a healthy person and also described each of the diseases and its side effects on various organs of an individual as well as other individuals in a colony and community with a significant interpretation of the condition of the individual(s).

19. The invention of claim one in which the information is analyzed by artificial intelligence and the results will be a kind of creation of new and correct knowledge based on digits and statistical numbers to minimize the error.

20. The invention of claim one in which if there is side effect or suspicion for the existence of the disease, according to the protocols approved by the medical community take tests or samples, and convert the results of each test into processable information on the main server of this place which these results assess by artificial intelligence in the form of numerical analysis or based on image processing according to modified machine algorithms and according to high accuracy in reviewing information and clarity and separation of images for artificial intelligence, results obtained from fusion of each individual’s data with the new results, can provide the most accurate diagnosis of the disease for the therapeutic physician.

21. The invention of claim one in which while presenting the correct treatment protocols, by entering the correct treatment methods applied on each individual, the progress of treatment and also the final results of the treatment method, by examining the colony of similar patients and treatment methods can provide the best method of treatment with the suitable limitations as the optimal treatment method to the physician.

22. The invention of claim one in which in case of need for surgery, a surgical process can be simulated based on the available data from the patient's body, genetic conditions, physiological elements, similar surgeries, as well as the diagnosis made on the patient with the help of artificial intelligence, and suggest the mentioned process as the surgery’s model to the physician considering various facilities and different methods.

23. The invention of claim one in which the possibility of presenting the media of the process can clarify the course of treatment and the process of future recovery before starting the treatment process.

24. The invention of claim one in which by fusion of each individual’s data and creating previous information chain system and also comparing the similar elements of the chains an inventive step takes regarding to integral analysis of existed diseases in a colony or a community and also the possibility to predict the epidemics and similar disease in colony increase.

25. The invention of claim one in which the chance to predict the disease and in particular reducing errors in diagnosis enhance.