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Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart...
Gray mold causes a sharp drop in blueberries production, the modeling and analysis of blueberry gray mold are important for the future study of blueberry related diseases and insect pests. In the introduction, the related diseases and insect pests of blueberry were summarized. The modeling method of blueberry pests and diseases was introduced. On this basis, the blueberry gray mold was modeled. And...
A brain-based neural network previously used to model short-term decisions from description is extended to decisions from experience — specifically, decisions by a retailer on how much of a product to purchase per day based on cost, price, discounts for large purchases, and feedback about demand on previous days. Learning from feedback is represented in the network by an analog of dopamine neurons'...
The conventional approach of generating clinical opinions from general blood test (GBT) results uses the deep neural network (DNN) comprised of fully-connected layers. The large number of input neurons and output neurons result in the complex DNN structure, which causes overfitting problem. However, the dimension of the input vector and the output vector cannot be reduced arbitrarily, as all GBT results...
In this paper, the authors investigated the main types of mammary dysplasia. In order to classify biomedical images, the researchers developed a basic model of convolutional neural network (CNN). Input parameters of the neural network to classify cytological and histological images were thoroughly researched and selected.
A large volume of data is steadily produced by the healthcare industry on daily basis. Data mining and machine learning approaches are two effective techniques applicable for data analysis and finding the hidden patterns which can be utilized for medical decision making. As the decisions in medical field are dealing with patient outcome, a high level of accuracy in data mining is needed. In this paper...
Gait Initiation Failure (GIF) is one of the most disabling gait disturbances seen in advanced Parkinson's disease (PD). Gait Initiation is a complex motor task that requires motor and cognitive processing to enable the correct selection, timing and scaling of movement. Failure to initiate the first step often precipitates falls and leads to significant morbidity. However, the brain mechanisms underlying...
In this article, the results of using neural network approach for solving hardly formalized task — diagnosing acute impairment of cerebral circulation, have been represented. Results of modeling neural network in the form of multilayer perceptron have been listed. The coefficients of diagnostic specificity, diagnostic sensitivity and diagnostic accuracy have been calculated.
This paper presents an approach for the medical diagnostics of pulmonary diseases condensate of moisture in exhaled air. A new approach is proposed which solves the problem of automated intelligent diagnostic using machine learning techniques. Our method runs in real-time and reaches the accuracy about 95%.
The power law in the frequency spectrum S(f) = 1/fβ allows for a good representation of the various time evolution and complex interactions of many physiological processes. The spectral exponent β can be interpreted as the degree of fractal characteristic which in turn makes it some sort of biomarker that gives an idea of the relative health of an individual. The prediction of the 1/fβ time series...
This paper presents a system for classification of asthma based on artificial neural network. A total of 1800 Medical Reports were used for neural network training. The system was subsequently tested through the use of 1250 Medical Reports established by physicians from hospital Sarajevo. Out of the aforementioned Medical Reports, 728 were diagnoses of asthma, while 522 were healthy subjects. Out...
Health information technology is spreading all over the world to provide right medical advice for healthcare. In this context, this paper describes the application of data mining techniques to identify jaundice by analyzing liver function test reports. Artificial neural network and support vector machine classifiers are employed here for classification on the basis of liver condition. Since correct...
Functional tissue regeneration after brain injury requires cell replacement for dead neurons and rebuilding neural networks. Since brain injury is not recovered spontaneously in general, breakthrough technologies have been awaited for neural replacement. To develop new techniques for neural replacement, our research team has examined the proliferation potency of neurons by biological approach and...
Mortality rate increases all over the world on a daily basis. The reason for this could be largely adduced to the increase in the number of patients with cardiovascular diseases. To worsen the case, many physicians have been known for misdiagnosis of patients reporting heart related ailment. In this paper, an intelligent system has been design which will help in effective diagnosis of the patient...
Anorexia nervosa is a quiet dangerous disease that detected in an early stage may save the patient life and flushes his veins with “passion-red blood” pumping happiness and hope with every heartbeat. A study based on back propagation neural network giving machines the ability to mimic the human function to detect a “haunted person by anorexia “ from a person obsessed by “looking “wow” as a model under...
Heart disease prediction is treated as most complicated task in the field of medical sciences. Thus there arises a need to develop a decision support system for detecting heart disease of a patient. In this paper, we propose efficient genetic algorithm hybrid with the back propagation technique approach for heart disease prediction. Today medical field have come a long way to treat patients with various...
A new methodology for improving the performance and training of neural network classifiers is presented. The main idea is based on using redundant classifiers in an ensemble in order to guarantee the best generalisation ability of the classifier. As compared to previous designs, a novel method for output combination based on weighted averaging is introduced. The proposed technique consist in considering...
Most of the Brain Computer Interface (BCI) techniques use EEG signals as a main source. Any BCI system consists of three modules and they are signal recorder, signal preprocessor and classifier. Development /Selection of efficient classifiers are a challenging task in this domain. The key work addressed in this paper is the classification of EEG signals measured under planning and relaxed state using...
Information Technology is playing a game changing role in life of human being. Healthcare is one of the prime concerns of every human being. This research work is based on diabetes, a chronic disease which is very common in all over the world. A decision support system may help doctors for decision-making and it may also support to an individual to take decision after filling the details of his or...
In medical field the diagnosis of heart disease is most difficult task. It depends on the careful analysis of different clinical and pathological data of the patient by medical experts, which is complicated process. Due to advancement in machine learning and information technology, the researchers and medical practitioners in large extent are interested in the development of automated system for the...
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