Ahmet Yardimci

Soft computing in medicine

Soft computing (SC) is not a new term; we have gotten used to reading and hearing about it daily. Nowadays, the term is used often in computer science and information technology. It is possible to define SC in different ways. Nonetheless, SC is a consortium of methodologies which works synergistically and provides, in one form or another, flexible information processing capability for handling real life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve tractability, robustness and low-cost solutions. SC includes fuzzy logic (FL), neural networks (NNs), and genetic algorithm (GA) methodologies. SC combines these methodologies as FL and NN (FL-NN), NN and GA (NN-GA) and FL and GA (FL-GA). Recent years have witnessed the phenomenal growth of bio-informatics and medical informatics by using computational techniques for interpretation and analysis of biological and medical data. Among the large number of computational techniques used, SC, which incorporates neural networks, evolutionary computation, and fuzzy systems, provides unmatched utility because of its demonstrated strength in handling imprecise information and providing novel solutions to hard problems. The aim of this paper is to introduce briefly the various SC methodologies and to present various applications in medicine between the years 2000 and 2008. The scope is to demonstrate the possibilities of applying SC to medicine-related problems. The recent published knowledge about use of SC in medicine is researched in MEDLINE. This study detects which methodology or methodologies of SC are used frequently together to solve the special problems of medicine. According to MEDLINE database searches, the rates of preference of SC methodologies in medicine were found as 68% of FL-NN, 27% of NN-GA and 5% of FL-GA. So far, FL-NN methodology was significantly used in medicine. The rates of using FL-NN in clinical science, diagnostic science and basic science were found as %83, %71 and %48, respectively. On the other hand NN-GA and FL-GA methodologies were mostly preferred by basic science of medicine. Another message emerging from this survey is that the number of papers which used NN-GA methodology has continuously risen until today. Also search results put the case clearly that FL-GA methodology has not applied well enough to medicine yet. Undeniable interest in studying SC methodologies in genetics, physiology, radiology, cardiology, and neurology disciplines proves that studying SC is very fruitful in these disciplines and it is expected that future researches in medicine will use SC more than it is used today to solve more complex problems.

Applications of Soft Computing to Medical Problems

The medical industry requires new engineering technologies, to assess information objectively. While recent developments in medical engineering have been achieved by state-of-the-art of intelligent computing techniques including computer-aided diagnosis, computer-aided radiography, developments in computational techniques including soft computing (SC), information processing and data mining hold new premises in this field. SC methods are becoming indispensable for to sport modern medical practice. SC combines Fuzzy Logic (FL), Neural Networks (NN), and Genetic Algorithms (GAs) methodologies. The aim of this paper is to introduce briefly the various SC methodologies and to present various applications in medicine between the years 2000 and 2008. The recent published knowledge about use of SC in medicine is researched in MEDLINE. According to MEDLINE database searches, the rates of preference of SC methodologies in medicine were found as 68% of FL-NN, 27% of NN-GA and 5% of FL-GA.

A survey on use of soft computing methods in medicine

The objective of this paper is to introduce briefly the various soft computing methodologies and to present various applications in medicine. The scope is to demonstrate the possibilities of applying soft computing to medicine related problems. The recent published knowledge about use of soft computing in medicine is observed from the literature surveyed and reviewed. This study detects which methodology or methodologies of soft computing are used frequently together to solve the special problems of medicine. According to database searches, the rates of preference of soft computing methodologies in medicine are found as 70% of fuzzy logic-neural networks, 27% of neural networks-genetic algorithms and 3% of fuzzy logic-genetic algorithms in our study results. So far, fuzzy logic-neural networks methodology was significantly used in clinical science of medicine. On the other hand neural networks-genetic algorithms and fuzzy logic-genetic algorithms methodologies were mostly preferred by basic science of medicine. The study showed that there is undeniable interest in studying soft computing methodologies in genetics, physiology, radiology, cardiology, and neurology disciplines.

Fuzzy logic based gait classification for hemiplegic patients

In this study a fuzzy logic classification system was used first to discriminate healthy subjects from patients rather than classifying those using Brunnstrom stages. Decision making was performed in two stages: feature extraction of gait signals and the fuzzy logic classification system which is used Tsukamato-type inference method. According to our signal feature extraction studies, we focused on temporal events and symetrical features of gait signal. Developed system has six inputs while four of them for temporal features evaluation rule block and two of them symmetrical features evaluation rule block. Our simulation test results showed that proposed system classify correctly 100% of subjects as patient and healthy elderly. The correlation coefficient was found 0.85 for classification to subjects to correct Brunnstrom stages. The results show that classifying patients becomes increasingly difficult linearly according to hemiplegias severity.

A Data-Mining Approach for Investigating Social and Economic Geographical Dynamics of

beta-Thalassemia is an anemic genetic disorder that remains a major global health issue, especially in the globalized era where public health, economics, and education are tightly interwoven. Previous studies have examined the diseases rate and heredity. This study analyzed beta-thalassemias socioeconomic geography and how it affects the afflicted population. We processed survey data and performed data mining using self-organizing maps to identify underlying data structure. We hypothesized that certain variables mark subgroups within the affected population and we aimed at identifying these subgroups and used a correlation-based measure to assess the variables importance to the subgroups distinction. The populations education level was one of the major factors that divided it into different subgroups. Our study showed that recurring patterns of specific variables separated the affected population into disparate subgroups based on their response to questionnaires. Future studies can use such tools to delve deeper into how other variables (e.g. socioeconomic and genomic) can identify subgroups within larger affected populations.

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Water quality management is an important issue of relevance in the context of present times. Water quality indices are computed for classification of water wherein the integration of parametric information on water quality data and the expert’s knowledgebase on their importance & weights are considered. Considerable uncertainties are involved in the process of defining water quality for specific usage. Antalya City, located along the coasts of Mediterranean Sea in Turkey, is famous worldwide due to its tourism potential. Antalya City has a beautiful landscape composed of mountains, forests, beautiful beaches and the sea. In order to apply sustainable tourism principles in Antalya, the protection of valuable environmental resources gains a particular importance. A land survey study was carried out to determine the pollution loads of Bogacay Stream, an important land-based pollution source of Antalya City, for one year duration. According to the water quality classifications obtained from Fuzzy Logic, water quality changes temporally in Bogacay Stream and an occasional critical level of water quality was determined in July which coincides with the peak use of the beach for recreational activities. Goksu Stream is the main source of Bogacay Stream. It always carries main part of water to Bogacay. So, on a large scale Goksu Stream determines the Bogacay Stream’s water quality.

-Thalassemia's Spread

This paper is the first step of a multi-sensor fusion system for control of dept of desflurane anesthesia. In this study, depth of desflurane anesthesia was examined through cardiovascular-based an adaptive neuro-fuzzy system according to changing in the blood pressure and heart rate taken from the patient. The second step, in the next paper will be based on auditory evoked responses. The system designed for anesthetic agent, desflurane, because it is very popular and among the first choices of anesthesiologist for inhalation anesthesia. Intraoperative awareness resulting from inadequate anesthetic is a rare but serious complication during general anesthesia. In order to prevent possible intraoperative awareness, anesthesiologists usually apply anesthetics at level much above the minimal necessary. Anesthetic overdosing prolongs the recovery period, which may cause severe hemodynamic depression and a life-threatening scenario in critically ill patients. To increase patient safety and comfort is one of the most important potential benefits of the system. The second important aim of the study is to relase the anesthesiologist so that he or she can devote attention to other tasks that can’t yet be adequately automated. Also, to make the optimum in the area of anesthetic agent and to economize by lessening the costs of an operation are included the benefits which are coming with this system.

A Fuzzy Logic Application to Environment Management System: A Case Study for Goksu Streams Water Quality Assesment

Therapeutic ultrasound is an emerging field with many medical applications. High intensity focused ultrasound provides the ability to localize the deposition of acoustic energy within the body, which can cause tissue necrosis and hemostasis. The ultrasound applied in therapy is usually ranged from 1MHz to 1000MHz. Even the least vibration of 1MHz would be as keen as a sharp knife to cut off steels, if we reinforce its amplitude. However, the output of the ultrasound used in treating people must be decreased substantially. A specific increase in temperature is necessary to achieve a temperature-mediated therapeutic impact by ultrasound in rehabilitation. On a large scale ultrasound intensity determines the temperature level on the tissue. High intensity causes a marked mechanical peak loading of the tissue. This may even lead to tissue damage. The extreme pressure differences developing as a consequence of exposure to ultrasound may cause cavitations in the tissues. Opinions in the literature on the duration of treatment also vary. The duration of treatment depends on the size of the body area to be treated. Lehmann fixes the maximum duration of treatment at 15 minutes. This refers to a treated area of 75–100 cm2 which he considers the maximum area that can reasonably be treated. New medical applications have required advances in biomedical equipment design and advances in numerical and experimental studies of the interaction of sound with biological tissues and fluids. In this study a fuzzy logic control system will be explained which was developed in order to obtain optimum ultrasound intensity and determine optimum treatment time during ultrasound therapy (UT). This system also increases patient safety and comfort during UT.

Depth Control of Desflurane Anesthesia with an Adaptive Neuro-Fuzzy System

Background Renal allograft dysfunction monitoring is mainly performed using the serum creatinine (SC) level, Doppler ultrasound (US), or renal biopsy. Recently proposed diffusion-based magnetic resonance imaging (MRI) methods have been explored as new, non-invasive tools for assessing renal function after transplantation. Purpose To investigate the value of fractional anisotropy (FA) measurements in the evaluation of acute rejection cases after renal transplant. Material and Methods Doppler US and MRI diffusion tensor imaging (DTI) were performed in 21 patients with graft dysfunction requiring graft biopsy after renal transplantation and in 21 patients with normal graft function. The MR examinations were performed on a 1.5-T MRI using two b-values (0 and 800 s/mm2). FA values were measured from the cortex and medulla of the transplanted kidney at the upper, middle, and lower poles. Results Twenty-one transplant patients diagnosed with acute rejection (Group 1) were compared to the control group of 21 transplant patients with normal graft function (Group 2). The measured FA values of the medulla were 0.19 ± 0.02 and 0.22 ± 0.05 (P = 0.017) for Groups 1 and 2, respectively. On the other hand, the measured FA values of the renal cortex were 0.18 ± 0.04 and 0.18 ± 0.04 (P = 0.97) for Groups 1 and 2, respectively. Conclusion The good correlation between the renal medulla FA values and allograft function shows that MR DTI has potential for non-invasive functional assessment of transplanted kidneys. On the other hand, the renal cortex FA values had no correlation with the allograft function.

Ultrasound Intensity and Treatment Time Fuzzy Logic Control System for Low Cost Effective Ultrasound Therapy Devices

In this study, it is aimed to obtain Patella T-Reflex kinesiologic parameters on spasticity patients by using image processing methods and thereby extracting objective data for the evaluation of spasticity patients. For this reason, the movement of Patella T-reflex response to knee joint was recorded with the help of a camera after three LED markers placed on the knee joint. For the correctness of the pattern of the movements, data were compared with two-axis goniometer of Biometric Ltd company and thereby it was shown that the reflex patterns are identical. Thereon, using the software we have developed, the Patella T-reflex kinesiologic parameters were calculated and data were obtained for objective evaluation of the Spasticity patients.