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MODERN SOCIETY & SCIENCE PROGNOSIS & ACHIEVEMENT
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The high incidence of diabetes mellitus (DM) and associated severe irreversible complications gives this disease global medical and social significance and determines the keen interest of researchers in a detailed analysis of this pathology. Diabetes mellitus, with all its complications, places a heavy economic burden both on the patients themselves and their families, as well as on the healthcare system and the national economy. A report from the International Diabetes Federation (IDF) estimates, over 425 million people currently suffer from diabetes, a third of whom are over 65. The number of people with diabetes is projected to rise to 629 million by 2045, although incidence has certainly begun to decline in some high-income countries. At the same time, an additional 352 million people with impaired glucose tolerance are at high risk of developing diabetes (IDF Diabetes Atlas, 8th ed.). Among a number of deeply studied complications of diabetes, a special place in clinical practice is taken by disorders of bone tissue remodeling, which contribute to the development of diabetic osteopathy (DO). The social significance of this complication is determined by its consequences - low-energy fractures of the vertebrae and the appendicular skeleton bones, characterized by a high level of disability and mortality, and taking the problem of diabetic osteopathy beyond a narrow specialty, making it the subject of extensive scientific research. According to WHO estimates, more than 8.9 million osteoporotic fractures occur annually in the world, approximately one in three women and one in five men over the age of 50 experience a low-traumatic fracture. The incidence of femoral neck fractures in people with type 1 diabetes is seven times, and in type 2 diabetes is 1.5 times higher than in the general population. Mortality in the first year after fracture reaches 37%. About 33% of patients remain bedridden, 42% have limited mobility, and only 31% of patients return to their original level of activity. Type 1 and 2 diabetes mellitus have unique and overlapping mechanisms for bone loss. The hyperglycemic factor present in diabetes affects the structure of bone matrix proteins, such as collagen I, through non-enzymatic glycosylation, which can reduce bone strength and increase the risk of low-energy fractures even with a visible absence of bone loss. Diabetes also activates inflammatory processes, affects electrolyte homeostasis, the concentration of calcitropic hormones, which further contributes to the development of destructive processes in bone tissue. Since the achievements of modern medicine significantly increase the life expectancy of patients, the risk of diabetic complications and, accordingly, osteoporotic fractures also increases. In this regard, the problem of early diagnosis of bone metabolism disorders, which allows initially build the correct management strategy, thereby preventing the severe consequences of this complication of diabetes, has led to the urgency of the problem, on the solution of which the present study is focused. This monograph reviews and analyzes the processes of reparative osteogenesis in type 1 and 2 diabetes mellitus. This made it possible to elucidate qualitative and quantitative characteristics of bone tissue, forming an idea of the activity of bone remodeling processes in diabetes mellitus. The main purpose of this monograph is to study the pathogenetic basis of changes in metabolic processes in bone tissue in type 1 and 2 diabetes mellitus, to describe the predictors of diabetic osteopathy for the development of methods for early screening of shifts in bone remodeling processes aimed at preventing the progression of this pathology. Based on the analysis of indicators affecting and related to bone metabolism, a specialized program based on artificial neural network (ANN) was developed and applied based on the results of a clinical study, which provides the clinician with the opportunity to make a right and timely decision on bone remodeling shifts to identify patients with destructive changes in bone tissue from among patients with diabetes. In addition, the monograph describes the result of a study conducted by the author with the construction of diagnostic algorithm for stratification of patients with diabetes-related changes in bone tissue, aimed at leveling the risk of developing low-traumatic fractures. Develop a structure and implement software for an intelligent decision support system using artificial neural networks, which allows predicting the values of indicators characterizing the qualitative and quantitative state of the bone based on the measurement results of a number of laboratory variables, for early diagnosis of the risks of structural and functional changes in bone tissue patients with diabetes. A mathematical model has been built based on the use of an intelligent clinical decision support system to obtain prognostic information about bone changes, which helps to identify persons at high risk of diabetic osteopathy from the general cohort of patients with diabetes mellitus. An individual approach to diagnosis using hybrid technologies for processing large amounts of data, increasing the efficiency of prediction within the framework of personalized medicine can give an individual prognosis for a particular patient using ANN. Analysis suggests that artificial neural networks can also be applied at the decision-making level in the field of forecasting. We found that ANN-based solutions applied at the decision-making level suggest the prospect of its use in situations involving complex, unstructured or limited information. Timely implementation of the developed methodology for the comprehensive diagnosis of metabolic disorders of bone stomp in diabetes will predict the progression of this complication and reduce the risk of low-traumatic fractures. On the basis of the study, a methodology was developed and an intelligent clinical decision support system based on artificial neural networks was developed, which allows predicting the values of indicators characterizing the qualitative and quantitative state of the bone according to the results of measurements of a number of laboratory variables, for screening patients with bone remodeling disorders from total number of patients with diabetes. The authorship of the method is documented by a copyright registration certificate (no. 10711) issued by the intellectual property agency of the Republic of Azerbaijan.
Title: MODERN SOCIETY & SCIENCE PROGNOSIS & ACHIEVEMENT
Description:
The high incidence of diabetes mellitus (DM) and associated severe irreversible complications gives this disease global medical and social significance and determines the keen interest of researchers in a detailed analysis of this pathology.
Diabetes mellitus, with all its complications, places a heavy economic burden both on the patients themselves and their families, as well as on the healthcare system and the national economy.
A report from the International Diabetes Federation (IDF) estimates, over 425 million people currently suffer from diabetes, a third of whom are over 65.
The number of people with diabetes is projected to rise to 629 million by 2045, although incidence has certainly begun to decline in some high-income countries.
At the same time, an additional 352 million people with impaired glucose tolerance are at high risk of developing diabetes (IDF Diabetes Atlas, 8th ed.
).
Among a number of deeply studied complications of diabetes, a special place in clinical practice is taken by disorders of bone tissue remodeling, which contribute to the development of diabetic osteopathy (DO).
The social significance of this complication is determined by its consequences - low-energy fractures of the vertebrae and the appendicular skeleton bones, characterized by a high level of disability and mortality, and taking the problem of diabetic osteopathy beyond a narrow specialty, making it the subject of extensive scientific research.
According to WHO estimates, more than 8.
9 million osteoporotic fractures occur annually in the world, approximately one in three women and one in five men over the age of 50 experience a low-traumatic fracture.
The incidence of femoral neck fractures in people with type 1 diabetes is seven times, and in type 2 diabetes is 1.
5 times higher than in the general population.
Mortality in the first year after fracture reaches 37%.
About 33% of patients remain bedridden, 42% have limited mobility, and only 31% of patients return to their original level of activity.
Type 1 and 2 diabetes mellitus have unique and overlapping mechanisms for bone loss.
The hyperglycemic factor present in diabetes affects the structure of bone matrix proteins, such as collagen I, through non-enzymatic glycosylation, which can reduce bone strength and increase the risk of low-energy fractures even with a visible absence of bone loss.
Diabetes also activates inflammatory processes, affects electrolyte homeostasis, the concentration of calcitropic hormones, which further contributes to the development of destructive processes in bone tissue.
Since the achievements of modern medicine significantly increase the life expectancy of patients, the risk of diabetic complications and, accordingly, osteoporotic fractures also increases.
In this regard, the problem of early diagnosis of bone metabolism disorders, which allows initially build the correct management strategy, thereby preventing the severe consequences of this complication of diabetes, has led to the urgency of the problem, on the solution of which the present study is focused.
This monograph reviews and analyzes the processes of reparative osteogenesis in type 1 and 2 diabetes mellitus.
This made it possible to elucidate qualitative and quantitative characteristics of bone tissue, forming an idea of the activity of bone remodeling processes in diabetes mellitus.
The main purpose of this monograph is to study the pathogenetic basis of changes in metabolic processes in bone tissue in type 1 and 2 diabetes mellitus, to describe the predictors of diabetic osteopathy for the development of methods for early screening of shifts in bone remodeling processes aimed at preventing the progression of this pathology.
Based on the analysis of indicators affecting and related to bone metabolism, a specialized program based on artificial neural network (ANN) was developed and applied based on the results of a clinical study, which provides the clinician with the opportunity to make a right and timely decision on bone remodeling shifts to identify patients with destructive changes in bone tissue from among patients with diabetes.
In addition, the monograph describes the result of a study conducted by the author with the construction of diagnostic algorithm for stratification of patients with diabetes-related changes in bone tissue, aimed at leveling the risk of developing low-traumatic fractures.
Develop a structure and implement software for an intelligent decision support system using artificial neural networks, which allows predicting the values of indicators characterizing the qualitative and quantitative state of the bone based on the measurement results of a number of laboratory variables, for early diagnosis of the risks of structural and functional changes in bone tissue patients with diabetes.
A mathematical model has been built based on the use of an intelligent clinical decision support system to obtain prognostic information about bone changes, which helps to identify persons at high risk of diabetic osteopathy from the general cohort of patients with diabetes mellitus.
An individual approach to diagnosis using hybrid technologies for processing large amounts of data, increasing the efficiency of prediction within the framework of personalized medicine can give an individual prognosis for a particular patient using ANN.
Analysis suggests that artificial neural networks can also be applied at the decision-making level in the field of forecasting.
We found that ANN-based solutions applied at the decision-making level suggest the prospect of its use in situations involving complex, unstructured or limited information.
Timely implementation of the developed methodology for the comprehensive diagnosis of metabolic disorders of bone stomp in diabetes will predict the progression of this complication and reduce the risk of low-traumatic fractures.
On the basis of the study, a methodology was developed and an intelligent clinical decision support system based on artificial neural networks was developed, which allows predicting the values of indicators characterizing the qualitative and quantitative state of the bone according to the results of measurements of a number of laboratory variables, for screening patients with bone remodeling disorders from total number of patients with diabetes.
The authorship of the method is documented by a copyright registration certificate (no.
10711) issued by the intellectual property agency of the Republic of Azerbaijan.
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