ABSTRACT
Background: The aim of this study was to investigate the effects of two types of quran voice, Majlisi or Tartil on IgA, IgM, IgG, C3, C4 and White Blood Cell count.
Methods and Materials: this study was conducted on 60 volunteer students in sabzevar university of Medical sciences. Subjects were divided randomly into 2 groups. In the first group, participants heard to Majlisi voice and in the second group, subjects heard to Tartil voice of Quran for 20 minutes. Blood sampling were done before and after Quran hearing. IgA, IgM, IgG, C3 and C4 were measured by SRID and kit method and white blood cell count was done by cell counter. Data were analyzed using SPSS16 software and U Mann Whitney and Kruskal Wallis tests.
Results: Hearing the Majlisi voice significantly increased the IgG [p=0.032], C3 [p=0.049] and C4 [p=0.004], but it did not change other factors. Hearing the Tartil voice rose significantly gust the IgG [p=0.008] and C3 [p=0.001].
Conclusion: The results of this study shows that hearing to both types of Quran voice [Majlisi or Tartil] can go up the immune system factors and inhance this to encountering some stressful and critical situations.
ABSTRACT
Human body temperature can be a natural index in diagnosing some diseases. Thermal imaging [Thermography], which works on the basis of infrared radiations, is a fast, non-invasive, non-contact and flexible method for monitoring human body temperature. Additionally, thermal imaging can map the body surface temperature in a non-contact manner. In recent years, extensive research has been conducted with the aim of increasing the use of thermal cameras and obtaining a close relationship between skin temperature and thermal physiology. Thermal imaging has been successful in diagnosing breast cancer, diseases related to blood pathology [e.g., arteriosclerosis, peripheral vascular disease, deep vein thrombosis, effects of vasoconstrictors such as nicotine] - diseases related to joint and bone pathology, and especially in tumoral pathology and pediatrics diseases. This paper investigates the function of thermal cameras, and capabilities and advantages of thermal imaging method in the diagnosis of various diseases.
ABSTRACT
Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA", which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration [FNA]. We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples [212 patient samples [malignant] and 357 healthy samples [benign]]. In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm [EA] with Genetic Algorithm [GA], and also used Exact Classifier Systems [here by Fuzzy C-Means [FCM]] to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks [NN] to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. According to Wisconsin Data Base Cancer [WDBC] data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%" on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration [FNA] can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples.