MEDIC
SINCE
ISSN: 2181-4155
Scientific journal 1 (1 ) 2022
DIAONOST'C HOSPtTAL
ISSN: 2181-4155
Ilmiy-amaliy jurnal NI (1) 2022
Bosh muharrir
Mamasadikov Nurillo Shukrullayevich — CAMI_J rektori Bosh muharrir o'rinbosari dotsent Normatova Shahnoza Anvarovna (Farg*ona) Tahrir hay'ati:
2
Scientjfvc јоигла! МЕТОIАН
MUNDARIJA
ПОВЫШЕНИЕ БИОЛОГИЧЕСКОЙ СОВМЕСТИМОСТИ ИМПЛАНТОВ НА
ОСНОВЕ Сп-Сге Ботпров М. Ш.,А., Мопа.жонов ММ», Минченя
СОВЕРШЕНСТВОВАНИЕ ЛАПАРОСКОПИЧЕСКОГО ДОСТУПА ПРИ ЛЕЧЕНИИ ПАЦИЕНТОК С ОБРАЗОВАНИЯМИ БОЛЬШИХ РАЗМЕРОВ В МАТКЕ. Н А.
РОЛЬ ФАКТОРОВ РИСКА В РАЗВИТИИ БРОНХИАЛЬНОЙ АСТМЫ В
ДЕТСКОМ ВОЗРАСТЕ (П ш-А.,
КамотовиД,А. 25
ФРАНЦУЗСКИЙ ПАРАДОКС: ДА? НЕТ? МОЖЕТ БЫТЬ? (Предварительный обзор по данным зарубежной печати). Сухинин А. А.» Онбыш Т, Е.»
Норматова Ш, А., Боптров М, Т, 31
АХОЛИ УРТАЧА КАЁт ДАВОМИЙЛИГИ УЗГАРИШИНИ КЕЛГУСИДАГИ
ТЕНДЕНЦИЯЛАРИНИ БАХОЛАШ. НИЛ, Манаризпе«ХО.,
Ш А., Эртштов НЭК60
МАСШТАБЫ РАСПРОСТРАНЕННОСТИ ГЕЛЬМИНТОЗОВ СРЕДИ
НАСЕЛЕНИЯ АЗЕРБАЙДЖАНА. Хатирп Н. Х., Рузиматова 71
С,ЕРАТТТ В l<ASALLlGINl DAVOLASHDA DORIVOR 0'SlMLIkLARDAN
OLJNADIGAN BIOLOGlk FAOL MODDALARM JIGAR HUJAYRASlGA TA'SlRlNI
0'RGANISH, B01irav М. Т., NormaIova „Sh.A.e kuranmtova Sh.A. ...............................ВЗ
ARTIFlClAL 1NTELLlGENCE lN MEDICAL DIAGNOSTICS. А.А.,
RiCjev ,Sh-I89
з
I
ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSTICS
HCIO'CCTBEHHb1V1 UHTEAJIEKT B MEAUUUHCKOM AHAVHOCTHKE
TIBBIY DIAGNOSTIKADA SUN'IY INTELTEKT
Ábdumanonov,4. .4v,
Associate Professor ofCentral Asian Medical University, ahror79Qnbox.ru /?uziev Sh./„
Professor ofTashkent Pedicaric Medical Institute,
Abstract: The paper discusses the prospects for the use of artificial intelligence technologies in healthcare. medico/ diagnostics and treatment to improve the quality and reliability ofpatient treatment, Artificial intelligence as a separaðe science Of information technology is also developing in the Weld ofgrain storage and is used in various fields of medicine. The use of artifìcia/ intelligence in medical information systems is provided with a specially compiled database of problema\ie and their signs for each area of medicine, as well' as knowledge base on the corresponding medical action. The paper considers a class of in\e//igeni systems thai solve the information problem of recognition and monitoring, presents a system focused on solving the problem of recognizing an emergency condition upon presentation Of' Signs Of' diseases, which should be under.Ýð00d as anamnes/ic, clinical and laboratory The use Of artificial intelligence in the diagnosiic process Wii/ increase the re/iabi/iïy of diagnostic support and increase the reliability ofclinical diagnostics in diagnostic decision suppor\ systems,
Key words: healthcare. medicine, intelligence, medico/ information sy,$/ejns, knowledge base.
Armoma«un: B cmanu,e
G 3òpaaoarpanenun.
naguemnoe. IIcçyccmae1i'Hbiù umnemepon omòeu,nan naysca me.ruuuoeuïð mayorre pa3ßuŒaemcw crþepe xpanel/lffl u pa;Y11ð9'HblX unrþop.1/auuonnbÎ-t oóecnequeaemcH cnet11/œb1*0 cocmaeqennoù õasoil npoõuenqm,vc cumyauuû u ux np1/3HUK0B no Komepemnoù oõuacmu a maw,owe õaaoù 3Hauuù no coomeemcnwyouveory Oeùcmeuyo. B pafiožne paeeuompeð/
30f)aqy cncmeuat opnemnupoacnman peuœline pacnoßli'aaamm neomuoojcl/oeo cocmonnun npu npeòb}iwuenuu npu3,'/0h'0ß 3aõo•eeauuÑ, not) KomopbL111/ caeðyem
89
R.woqedbfe cnoaa: 3òpaaooxpaneuue, .ueðuguna, ucwyccmeeH1/bðù
Annotatsiya: Maqolada sun 'hy inÍe//ekt texnologiyu/aridan sog'/iqnj saq/ash, tibbiy diagnosÍika va davo/ashda bemorlarga xizmai ko'rsa/ish Mfati va ishonch/i/igini oshirish uchun foydolanish istiqbollari qi/inodi.
inrellekt axboro/ rexnologwa/arining alohida fan/ sif01ida libbiyraning soha/arida qo'//ani/adi hamda qish/oq xo'Ja/igi .sohasida ham rivoJ/anmoqda. Tibby axboro/ tizim/arida sun"y inte//ekfdanfoydalanish /ibbyotning har bir uniq sohasi muammo/i vaziyatlar va Warning helgi/arining tuzilgan shuningdek, legishli /ibþiy haraka//ar bo'yicha bilim/ar þa:asi bi/an ia'minlanadi. Maqo/ada aniq/ash va monitoring qi/ishning axhomr muammosini ha/ qi/adrgan aqlli /i:unlar sinfì ko'rib c/nqi/adi, anamnestlk, k/inik va laboratoriya ko trinish/ari tushuni/ishi kerak bo t/gan kasa//ik belgilari paydo ho 'Igandafavqulodda Olish ha/ qi/ishga qarðð/i/gan li:im taqdñn etiladi. Diagnostika Jorayonida ih/ellek/dun foydalanish diagnostik yordamning ishonch/i/igini oshiradi va diagnosÍika qaror/arini qo'//abquvvailash tizim/arida klinik diagnosÍika ishonch/iligini os/nradi,
Kalit so'zlar: sog'liqni saqlash, /ibbiyot, sun tiy intellek/, tibbiy li:imlari, bilimlar ba:asi.
Recently, there has been an increasing interest in artificial intelligence, caused by increased requirements for information systems, We are steadily moving towards a new information revolution, comparable in scale to the development of the global set, whose name is artificial intelligence,
Artificial Intelligence (Al) is a field of research that aims to study and model the principles and mechanisms of human intellectual activity. Al as a science is located at the Intersection of computer science, linguistics, psychology and philosophy. In addition, specific specialized knowledge from the relevant field is also used in the areas of Al application, such as natural sciences, law, economics, and medicine.
The idea of creating an altificial human likeness to solve complex problems and simulate the human mind has been in the air since ancient times. For the first time, the idea of creating an artificial human likeness was expressed by R. Lully (c, 1235-c. 1315), who in the X]V century tried to create a machine for solving vafious problems based on the universal classification of concepts [91.
In the eighteenth century; G, Leibniz (1646-1716) and R. Descartes (15961650) independently developed this idea by proposing universal classification languages for all sciences, These ideas formed the basis of theoretical developments in the field of creating afiificial intelligence, The birth of artificial intelligence as a scientific field occurred only after the creation of computers in the 40s of the XX century. At the same time, Norbert Wiener created his seminal works on the new science of cybernetics,
Researchers working in the field of Al have found that they are grappling with veuy complex problems that go far beyond traditional computer science. It turned out, that pnmary it is necessary to understand the mechamsms of the learmng process, the nature of language and sensory perception. It turned out that to create machines that mimic the of the human brain, you need to understand how billions of its interconnected neurons work Most of the researchers came to the conclusion that perhaps the most difficult problem facing modern science is to understand the processes of functioning of the human mind and not just imitate its worka which directly affected the fundamentål theoretical problems of psychological science.
Indeed, It is difficult for scientists to even come to a single pomt of view regarding the very subject of their research - intelligence, Some believe that intelligence is the ability to solve complex problems; others consider it as the ability io learn, genera/i:e and analogize; still others - as the ability to interact with the ouÍMde world through communication, perception and awareness of what is perceived.
Nevertheless, many Al researchers are inclined to accept the machine intelligence test proposed in the early 50s by the outstanding English mathematician and computer scientist Alan Turing A computer can be considered intelligent, Turing argued, if it can make us believe that we are not dealing with a machine, but with a person.
Currently there are six main areas of Al research:
knowledge representation; manipulation or knowledge and search for solutions; communication systems;
perception systems.
machine learning; modeling intelligent behavior.
The emergence of Al as a scientific field is associated with an increase in the capabilities of computer technology and increased requirements for the mathematical support of computers. Many scientists consider Arthur Turing as the founder, In 1950 Turing's article "Computing Machinery and
English magazine) offers a criterion for whether a machine has thinking abillties (Turing test).
Medical diagnostics refers to the dynamic and clinical diagnosis process is vital', if developers do not understand the diagnostic process correctly, then it is no less likely that they may develop any used software in medical diagnostics. A clinical diagnosis is specialized knowledge that can only be understood correctly with some essential medical knowledge- Doctors study the diagnostic process using knowledge from many medical branches such as human anatomy, medical biochemistry, medical physiology; pathology, microbiology, parasitology, fonensic medicine, medicine, epidemiology, surgery, ENT, ophthalmology, pediatrics, radiology, pharmacology, and forensic medicine, Ideally, the developer should have some knowledge in these medical industries. Although there are many defined principles and guidelines for medical diagnosis, the diagnostic process is still seen as an an form that can only be learned through medical knowledge and experience. Doctors' help in the development process is very important, Choice of clinical situations, if you want to develop a clinical diagnostic system that solves all medical diagnostic processes (for example, requesting a patient, examining a patient, taking ultrasound images, X-rays and processing them, and so on), you will probably never need to release a product until you have an infinite number of resources Il I, 12, 171
Choosing a clinical area is very important, Selecting a small area results in developing a small tool; while selecting a very large clinical area and domain will be difficult to develop and require a huge amount of resources and decades of human life. Commercial suppliers should analyze the commercial value of the product. At the moment, clinical diagnosis support systems are not very successful in the commercial software marketi Even if it is most ma]or clinical trials are suppofied151,
The architecture of a typical expert system includes the following main components: a knowledge base (KB); database (DB); a goal base; a working memoty or working knowledge base; a decision inference stibsystem; intelligent interface subsystem; a support and debugging subsystem; a digital modeling subsystem; a decision explanation subsystem; and a coordination and management subsystem
The main task of intelligent systems is knowledge processing. Most often, intelligent systems are used to solve complex problems, where the main complexity of the solution is associated with the use of poorly formalized knowledge of practitioners, and where logical (or semantic) information processing prevails over computational. For example, understanding natural language, analyzing visual information, supporting decision-making in difficult situations, making a diagnosis, and making recommendations on treatment methods 19, I l
12, 18, 20, 211,
One of the most important problems is the problem of knowledge representation, This is explained by the fact that the form of knowledge representation has a significant impact on the characteristics and properties of the system, In the natural and technical sciences, the following traditional way of presenting knowledge is adopted. In natural language, the basic concepts and relations between them are introduced. In this previously defined concepts and relationships are used, the meaning of which is already known, Next, a
correspondence is established between the characteristics (most often quantitative) ofthe concepts ofknowledge and the appropriate mathematical model.
Knowledge may not always be described accurately - so-called "fuzzy" knowledge is often encountered, When trying to formalize human knowledge, researchers soon encountered a problem that made it difficult to use traditional mathematical tools to describe it, There is a whole class of descriptions that use qualitative charactenstics of objects: many; few, strong¼ velY strong, and so on, These charactenstics are usually vague and cannot be clearly intemreted, but they contain important information, such as" One possible sign of tick-borne encephalitis is a high temperature,
Approximate Theory.
The theolY of approximate reasoning was created by Lofty Zadeh in 1979. This theolY provides a powerful tool for implementing logical inference with fuzzy and uncertain information. The central idea of this theory is to represent logical statements in the form of statements that assign fuzzy sets to variables as values
[91,
At the initial stage of intellectuallzatlon of medlcal information systems (MIS), we, together with experienced doctors in the relevant fields of medicine, created and implemented in clinical practice a system for intellectual support of the doctor during the examination of patients similar to 119L but for urgent pathologies, At the same time, we have developed BZS of this system for the areas of emergency abdominal surgery and emergency medicine that operate in a multidisciplinary hospital,
Taking into account the fact that B timely and prompt identification (forecasting)is of paramount importance in emergency medicine- life-threatening emergency condition-problem situation (I'S), as well as taking adequate emergency measures to eliminate them, we have developed methods, algorithms and software for automatic detection of PS in the patient's body from the data of his electronic medical history (EIB), as well the implementation of intellectual support for medical services in the next stage of the MIS intellectualization process solutions to get out of this situation, Naturally, such situations have different natures in different pathological conditions of organs and the body as a whole and require appropriate adequate approaches to their elimination,
Such developments are relevant and necessary especially for the fields of medicine, where the elements or subjectivity are very significant, and the responsibility for making decisions is great, which is typical, in for surgeuy, especially for emergency abdominal surgery.
The paper considers a class of intelligent systems that solve the information problem of recognizing, monitorong a problem situation, and selecting the level of assistance from available resources that would ensure the minimum probability of
• plannmg a chain of events from the current state of the patient to the desired result (recovery) for a given treatment program; assessment of information on the degree of materiality and their corresponding sotting under the specified criteria for selecting information;
• search for medical solutions in the context of incomplete and unclear information, using the specified "heuristics" and the experience of subject area experts.
As a result of the operation of the smart module, three types of situations can be identified,
I
• the first type of situations when there is an objective need for urgent adoption of an appropriate specific medical decision, taking into account the patient's condition;
• the second type of situation, when it is predicted that some medical decision will need to be made urgently in order to prevent the occurrence of the first type of situation in the future;
• the third type of situation is when there is no need to make a medical decision, and the doctor simply takes note of the results of the analysis of information,
If the first two types of situations can be formalized in order to automatically detect such situations and develop a certain set of optimal medical decisions, then the third type of situations is difficult to formalize, since the doctor is not to make any decision,
To detect PS, the existing medical information system must be supplemented with a subsystem with the following modules:
• modules for entering and correcting signs of PS, as well as corresponding sets of medical decisions;
• PS detection module; a module for selecting a set of optimal medical decisions and, in some cases, making (executing) these decisions; module for evaluating the effectiveness of decisions made; a module for maintaining a history for each specific PSS and if necessa1Y, l•sr it in the future when making a decision,
The functioning of the support system is provided by a specially compiled database of problem situations and their signs, for each specific field of medicine, as well as a knowledge base on relevant medical actions. The main task in building the system of intellectualization of MIS, of course, is to create a database
containing infomtation about the relationship of signs of the patient's body with certain problem situations [13-171
When creating the database and BZ of the system developed by us, we used the features of the clinical picture in various PS identlfied as a result of analyzing the medical history of 388 patients operated on in the emergency department of abdominal Surgery of the Ferghana branch of the Reptiblican Center for Emergency Medical Care in the period 2007-2012. They present the identified PS and their relationship with various signs of the body's condition. Out of 388 patients with abdominal acute surgical diseases that thneaten the patient's life, PS occurred in 76, including 65, associated with the development of various complications of the underlying disease, such as acute diffuse purulent peritonitis, bleeding, post-hemorrhagic or post-traumatic shock, hypovolemic shock, acute cardiovascular, respiratory failure, liver failure, etc. 11 patients with lifethreatening PS developed non-underlying pathologies associated with anaphylactic shock or concomitant pathologies such as CHI), diabetes mellitus, chronic nonspecific lung disease, etc. In 37 patients with PS, a life-threatening condition of the patient occurred preoperatively, 38 patients in the postoperative period, The number of signs in the form of precursors of PS was 96, reliable signs including complaints or patients, objective data and results or instrumental and laboratory studies were 502. The clinical manifestation of life-threatening PS in the patient was characterized mainly by a sham drop in blood pressure, cardiac arrhythmia, tachycardia, bradycardia, respiratory anhythmia, convulsive state, loss of consciousness, hypefihermia, hypovolemia and also a corresponding change in laboratory criteria.
In the process of functioning of the subsystem "Intellectualization or medical decisions", the main source of primary and reference information is the electronic patient history data contained in the MIS. At the same time, the subsystem maintains its own database, where the following data is stored:
• a list of all registered pss in the system;
signs that can be used to detect PS-
• a set of optimal medical solutions for the resolution of a specific PS;
• criteria that should be used to evaluate the effectiveness of individual solutions to elimmate a specific PS; hist01Y of medical decisions made for each specific PSE
When entering a new PS into the system, first of all, you must specify the signs by which the PS detection module would be able to recognize this PS, The next step when entering a new PS into the knowledge base is to establish a specific set of medical solutions to eliminate this problem.
To implement the above methodology, algorithms for detecting PS were compiled from the patient's medical history data and a BZ for clinically justified optimal medical actions in these situations was developed. has been created that implements the functioning of the developed subsystem in the MIS structure, An automated workplace of an expert doctor with a user-friendly interface has been developed, and the previously created doctor's workstation has been supplemented With a special dialog for the doctor to interact with the system.
With the inclusion of the subsystem "Intellectualization of medical decisions" in the MIS, the technology of solving medical and diagnostic problems is radically changing, If with traditional technology, a doctor starts searching for solutions only after a certain PS occurs and, as a rule, in conditions or an acute shonage of time, then in intelligent information systems, a specialist doctor can form a knowledge base on PS in advance With the help of an expert doctor's workstation developed by us, without haste and thoroughly, and in the future the system itself will monitoring the occurrence of PS and the search for acceptable medical solutions [51, At the same time, a problem entered into the knowledge base can be solved repeatedly as it occurs. Moreover; taking into account the results of previous solutions, the system gradually becomes not only more experienced, but even "smartn with the expansion of the knowledge base.
This approach to the intellectualization of medical decision-making processes makes It possible to make significant changes in the technology of developing intelligent systems to support the doctofls activities. Now it is enough for developers to create tools that allow a specialist from any field of climcal medicine-an expert'to create and maintain their own database and knowledge on PS. And, finally• following the ramous thesis that it is necessary to give the machine-the machine, the person-the human, the proposed intelligent information system provides for an optimal distribution of responsibilities in the decision, making process between the system and the doctor, Medical specialists form databases of data and knowledge in their field and make the final decision, and the system will do all the other complex computational, analytical and logical work, The main advantages of the proposed approach to intellectualization of medical decision-making processes are:
• development of a single tool for solving many non-standard problems in various areas of medicine;
• during the operation of information systems, self-learning of the system With the replenishment of the knowledge base also takes place;
• flexibility in solving problems by combining ready-made and proven medical solutions;
• the implementation of the intellectualization module does not require stopping or redesigning the existing information system.
Thus, the *'intelligent support" system by us, which contains two databases and KB and two software blocks, using clinical information from the MIS patient's electronic medical history database, provides prediction and recognition of problematic situations in the patient's body, in particular with abdominal emergency surgical pathology, and contributes to making effective medical decisions to eliminate them or prevention,
The experience of recent years has shown that applying one method to solve complex problems and problems does not always lead to success, In a hybrid
architecture that combines multiple paradigms, the effectiveness of one approach can compensate for the weakness of the other, By combining diffenent approaches, you can avoid the disadvantages inherent in each of them individually, Therefore, one of the leading trends in modern computer science is the development of integrated, hybrid and synergistic systems. Such systems consist of various elements (components) combined to achieve their goals. Integration and hybridization of various methods and technologies allows you to solve complex problems that cannot be solved on the basis of any individual methods or technologies.
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