RESUMEN
The study aims to enhance the standard of medical care for individuals working in the electric power industry who are exposed to industrial frequency electromagnetic fields and other relevant risk factors. This enhancement is sought through the integration of fuzzy mathematical models with contemporary information and intellectual technologies. The study addresses the challenges of forecasting and diagnosing illnesses within a specific demographic characterized by a combination of poorly formalized issues with interconnected conditions. To tackle this complexity, a methodological framework was developed for synthesizing hybrid fuzzy decision rules. This approach combines clinical expertise with artificial intelligence methodologies to promote innovative problem-solving strategies. Additionally, the researchers devised an original method to evaluate the body's protective capacity, which was integrated into these decision rules to enhance the precision and efficacy of medical decision-making processes. The research findings indicate that industrial frequency electromagnetic fields contribute to illnesses of societal significance. Additionally, it highlights that these effects are worsened by other risk factors such as adverse microclimates, noise, vibration, chemical exposure, and psychological stress. Diseases of the neurological, immunological, cardiovascular, genitourinary, respiratory, and digestive systems are caused by these variables in conjunction with unique physical traits. The development of mathematical models in this study makes it possible to detect and diagnose disorders in workers exposed to electromagnetic fields early on, especially those pertaining to the autonomic nervous system and heart rhythm regulation. The results can be used in clinical practice to treat personnel in the electric power industry since expert evaluation and modeling showed high confidence levels in decision-making accuracy.
Asunto(s)
Campos Electromagnéticos , Lógica Difusa , Enfermedades del Sistema Nervioso , Humanos , Campos Electromagnéticos/efectos adversos , Enfermedades del Sistema Nervioso/diagnóstico , Enfermedades del Sistema Nervioso/etiología , Bioingeniería , Exposición Profesional/efectos adversosRESUMEN
Currently, intelligent systems built on a multimodal basis are used to study the functional state of living objects. Its essence lies in the fact that a decision is made through several independent information channels with the subsequent aggregation of these decisions. The method of forming descriptors for classifiers of the functional state of the respiratory system includes the study of the spectral range of the respiratory rhythm and the construction of the wavelet plane of the monitoring electrocardiosignal overlapping this range. Then, variations in the breathing rhythm are determined along the corresponding lines of the wavelet plane. Its analysis makes it possible to select slow waves corresponding to the breathing rhythm and systemic waves of the second order. Analysis of the spectral characteristics of these waves makes it possible to form a space of informative features for classifiers of the functional state of the respiratory system. To construct classifiers of the functional state of the respiratory system, hierarchical classifiers were used. As an example, we took a group of patients with pneumonia with a well-defined diagnosis (radiography, X-ray tomography, laboratory data) and a group of volunteers without pulmonary pathology. The diagnostic sensitivity of the obtained classifier was 76% specificity with a diagnostic specificity of 82%, which is comparable to the results of X-ray studies. It is shown that the corresponding lines of the wavelet planes are correlated with the respiratory system and, using their Fourier analysis, descriptors can be obtained for training neural network classifiers of the functional state of the respiratory system.
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Redes Neurales de la Computación , Sistema Respiratorio , HumanosRESUMEN
This work aims at improving the quality of health assessments, specifically under the influence of occupational risk factors. For this purpose, additional informative indicators are utilized in prognostic and diagnostic models. The models are used to characterize the level of body protection based on oxidative status. A quantitative method is proposed to assess the body's level of protection by means of the levels of lipid peroxidation and antioxidant activity, which characterize the body's oxidative status. A mechanism is developed for integrating the proposed method into prognostic and diagnostic decision rules. The developed rules are in the form of mathematical models used to synthesize hybrid fuzzy decision rules, which are then used to quantify the level of body protection (LBP) against external risk factors, based on the use of protection level functions in terms of lipid peroxidation and antioxidant activity. A mechanism for embedding LBP into predictive and diagnostic decision rules has been proposed. The proposed method is used to predict the occurrence and development of coronary heart disease in railroad locomotive drivers. It was found that to improve the predicting and diagnosing of diseases caused by external pathogenic factors, quantitative assessments of LBP, determined by oxidative status, can be implemented. It has been established that the use of the protection level indicator in predictive decision rules makes it possible to increase the efficiency of the prediction while simultaneously increasing its accuracy.
Asunto(s)
Antioxidantes , Oxidantes , Humanos , Antioxidantes/metabolismo , Factores de Riesgo , Peroxidación de Lípido , PronósticoRESUMEN
One of the key echographic signs of focal pathology of the pancreas is the presence of formation contours and their nature. Endoscopic ultrasonography has a unique ability to visualize the echographic texture of the pancreatic parenchyma, and also allows you to assess in detail the boundaries and nature of the contours of the tumor formations of the organ due to the proximity of the ultrasound sensor. However, the differential diagnosis of focal pancreatic lesions remains a difficult clinical task due to the similarity of their echosemiotics. One of the ways to objectify and improve the accuracy of ultrasound data is the use of artificial intelligence methods for interpreting images. Improving the quality of differential diagnosis of focal pathology of the pancreas according to endoscopic ultrasonography based on the analysis of the nature of the contours of focal formations using fuzzy mathematical models.
Asunto(s)
Neoplasias Pancreáticas , Pancreatitis Crónica , Humanos , Endosonografía , Diagnóstico Diferencial , Inteligencia Artificial , Pancreatitis Crónica/diagnóstico por imagen , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/patología , Neoplasias PancreáticasRESUMEN
Several researchers studied the health impacts of electromagnetic fields in work environment. However, the previous research focuses on the statistical analysis of past exposure. There are no studies that addressed prediction of health symptoms. Prediction and early diagnosis of occupational diseases of electric power workers with acceptable accuracy is needed. The objective of this study is to develop a data driven mathematical model for predicting and diagnosis of occupational diseases in workers in electric power industry. The complex nature of disease occurrence due to electromagnetic radiation is appropriate for the fuzzy rules set by medical experts which are analyzed and validated to produce hybrid fuzzy decision rules. The selected group of medical experts suggested using hormonal disorders, endocrine diseases, coffee abuse, chronic diseases of the internal organs, allergic diseases, cervical osteochondrosis, severe course of infectious diseases, intoxication, injury. The developed hybrid fuzzy logic model predicts high risk of developing nervous system diseases. The prediction accuracy exceeded 0.88, which is acceptable for supporting tool.
RESUMEN
Urologists and nephrologists attribute pyelonephritis of pregnant women to the category of complicated upper urinary tract infections that threaten the development of a severe purulent-septic process. The frequency of pyelonephritis in pregnant women ranges from 12.2 to 33.8%. In this research, laboratory indicators of the state of immunity and lipid peroxidation using fuzzy decision logic are used to improve the quality of differential diagnosis of serous and purulent pyelonephritis in pregnant women. A space of informative indicators was formed that characterize the state of immune changes, making it possible to carry out the differential diagnosis of pyelonephritis forms in pregnant women with high accuracy. Results of the operation of the obtained decision rules in the control sample showed that the diagnostic efficiency of the proposed method reaches 93%, which is acceptable for use in medical practice.
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Mujeres Embarazadas , Pielonefritis , Diagnóstico Diferencial , Femenino , Lógica Difusa , Humanos , Embarazo , Pielonefritis/diagnósticoRESUMEN
The study focuses on the choice of prevention schemes of the appearance and recurrence of gangrene of the lower extremities, depending on any of the degrees of confidence that the patient will have gangrene or will experience its relapse. The degree of confidence is determined using the fuzzy logic of decision making on the relevant membership functions. For each of the selected classes, an appropriate prevention scheme has been developed, the effectiveness of which was tested using the theory of measuring latent variables and the synthesis of mathematical models of their choice depending on the degree of risk of the occurrence and recurrence of lower extremities gangrene. Model statistical tests showed that compared with traditional prevention schemes the use of the proposed models can increase the rate of positive results in the absence of lower extremities gangrene and reduce the possibility of relapse (recurrent changes by 42%, risk of amputation by 35%).
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Gangrena , Extremidad Inferior , Amputación Quirúrgica , Lógica Difusa , Gangrena/prevención & control , Gangrena/cirugía , Humanos , RecurrenciaRESUMEN
Many theories of reflexology use ancient concepts which do not coincide with the modern medical terminology of anatomy, physiology and biophysics. This substantially reduces the trust of physicians in reflexology methods. During this research, several mathematical models for the interaction of the internal and biological active points of meridian structures have been proposed. The analysis of these models allows the specification of a list of gastric diseases for which reflex diagnostics and reflex therapy methods are most effective and also allows increasing the effectiveness of these procedures. It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.
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Puntos de Acupuntura , Toma de Decisiones , Lógica Difusa , Úlcera Gástrica/fisiopatología , HumanosRESUMEN
We propose a biotech measurement scheme and software based on new features for the diagnosis of backbone osteochondrosis. Together with the traditional methods of diagnosis, the energy characteristics of biologically active points (acupuncture points, or APs) are used. This new software is based on mathematical models of the internal and biologically active points of meridian structures' interaction. The information from the APs is used in the solving rules based on fuzzy logic for decision-making, together with the factors of confidence of Shortliffe, the membership functions of Zadeh, and Kullback's informativeness measures. In terms of prognostic decision rules, clinical test shows that the quality of prediction using only the energy characteristics of APs is high, with high coefficient of confidence for the control sample as well. A check on control samples allows us to recommend the obtained results for use in medical practice as a part of corresponding systems of support for decision-making.
Asunto(s)
Sistemas de Apoyo a Decisiones Clínicas , Diagnóstico por Computador/métodos , Lógica Difusa , Vértebras Lumbares , Reconocimiento de Normas Patrones Automatizadas/métodos , Programas Informáticos , Osteocondrosis de la Columna Vertebral/diagnóstico , Humanos , Osteocondrosis , Pronóstico , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
Many theories of reflexology use ancient concepts which do not coincide with the modern medical terminology of anatomy, physiology and biophysics. This substantially reduces the trust of physicians in reflexology methods. During this research, several mathematical models for the interaction of the internal and biological active points of meridian structures have been proposed. The analysis of these models allows the specification of a list of heart diseases for which reflex diagnostics and reflex therapy methods are most effective and also allows increasing the effectiveness of these procedures. It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.
Asunto(s)
Puntos de Acupuntura , Cardiopatías/diagnóstico , Algoritmos , Ingeniería Biomédica , Diagnóstico por Computador , Lógica Difusa , Humanos , Valor Predictivo de las PruebasRESUMEN
A great number of reflexologies use ancient concepts that do not coincide with modern medical terminology of anatomy, physiology, and biophysics, substantially reducing the trust of today's physicians in this direction of their profession. Recently, several mathematical models of internal and biological active points of meridian structures interaction have been proposed. These models allowed specification of diseases for which reflex diagnostics and reflex therapy methods are most effective and also increased the efficacy of these procedures. Good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.