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Prediction with liigh reliability is very important in solving real-world problems, especially those that affect public health. The statistical properties of complex problems such as Covid-19 disease constantly change over time which makes modeling of such problems associated with high-level uncertainty. It has been proven that the type-2 fuzzy logic has the potential for modeling uncertainty to solve complex problems. In this research, for the first time, an intelligent method based on the capability of type-2 fuzzy logic was presented to manage uncertainty in predicting short-term and long-term time series in environmental crises such as the Covid-19 pandemic. The performance of the proposed model was evaluated using a real dataset collected from official sources. The results confirm the high efficiency of the proposed method on Covid-19 based on a ROC curve analysis. The obtained results showed an efficiency of 93.81٥/٠ for short and 91.33٥/٠ for long-term time series. This indicates the liigh efficiency and capability of the proposed model for managing uncertainty in predicting patterns of Covid-19 in comparison with similar methods. The proposed model can be useful to take strategic decisions and prevent the consequences of the Covid-19 epidemic in the short and long terms. [ABSTRACT FROM AUTHOR]

Background: 90Y and 177Lu are two well-known radionuclides used in radionuclide therapy to treat neuroendocrine tumors. Objective: This current study aims to evaluate, compare and optimize tumor therapy with 90Y and 177Lu for different volumes of the tumor using the criterion of self-absorbed dose, cross-absorbed dose, absorbed dose profile, absorbed dose uniformity, and dose-volume histogram (DVH) curve using Gate Monte Carlo simulation code. Material and Methods: In our analytical study, Gate Monte Carlo simulation code has been used to model tumors and simulate particle transport. Spherical tumors were modeled from radius 0.5 to 20 mm. Tumors were uniformly designed from water (soft tissue reagent). The full energy spectrum of each radionuclide of 177Lu and 90Y was used in the total volume of tumors with isotropic radiation, homogeneously. Self-absorbed dose, cross-absorbed dose, absorbed dose profile, absorbed dose uniformity, and DVH curve parameters were evaluated. Results: The absorbed dose for 90Y is higher than 177Lu in all tumors (p-value <5%). The uniformity of the absorbed dose for 177Lu is much greater than 90Y. As the tumor size increases, the DVH graph improves for 90Y. Conclusion: Based on self-absorbed dose, cross-absorbed dose, absorbed dose uniformity, and DVH diagram, 177Lu and 90Y are appropriate for smaller and larger tumors, respectively. Next, we can evaluate the appropriate cocktail of these radionuclides, in terms of the type of composition, for the treatment of tumors with a specific size. [ABSTRACT FROM AUTHOR]

Application of soft computing hybrid models have been concentrated to cope with uncertainty in the medical expert systems, recently. Heart disease is one of the mortal diseases that can be controlled in early stages. In this paper a hybrid Fuzzy-GA model for the Heart Disease Prediction (HDP) problem has been proposed. For this, first a Fuzzy Expert System (FES) using Mamdani model was presented. Then the membership functions parameters of the FES were optimized using the hybrid Fuzzy-Genetic Algorithm (Fuzzy-GA). The reason of selecting fuzzy method was its high potential to address the uncertainty sources in the knowledge of medical experts. Performance of the FES and Fuzzy-GA model were evaluated using a real dataset of 380 patients collected from Parsian Hospital in Karaj, Iran. Accuracy of the designed FES before optimization was 85.52%. After optimization using the hybrid Fuzzy-GA, the accuracy of this system was increased to 92.37%. The proposed hybrid model competes with its counterparts in terms of interpretability and accuracy in prognosis process of the heart disease. This model is promising for early diagnosis of the heart disease and saving more people lives. [ABSTRACT FROM AUTHOR]

Introduction: In myocardial perfusion imaging, reducing the number of photons in images of obese patients causes poor image quality. To solve this problem, we need to inject the tracer according to the patients' weight. Therefore, this study aimed to investigate the relationship between myocardial photon counts with patients' weight, BMI, and gender., Materials and Methods: A total of 129 patients underwent myocardial perfusion imaging in a twoday stress-first protocol, but only rest images were included in this study. Multiplication factor was used to determine the amount of radiopharmaceutical activity injected into the patients. For evaluating the effect of gender, the photon counts of 22 female patients were also assessed when the breast tissue was pulled upward (Breast Up). The total myocardial detector counts in the raw images were calculated from the summation of 32 projections. A multiple linear regression test was used to simultaneously examine the effects of weight, BMI, and gender on photon counts., Results: There was no significant relationship between photon counts and patients' weight (p=0.129) and BMI (0.406), but gender had significant effects on photon counts, and myocardial detector counts were found to be higher in males (p=0.00). There was a statistically significant difference between the images of Breast Up and Non-Breast Up, and myocardial detector counts were higher in the Breast Up imaging method (p=0.00)., Conclusion: Using the bodyweight formula, the image quality was comparable in obese and lean patients, but myocardial detector counts were lower in females, and this formula needs to be adjusted according to the patient's gender., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: 90 Y and 177 Lu are two well-known radionuclides used in radionuclide therapy to treat neuroendocrine tumors., Objective: This current study aims to evaluate, compare and optimize tumor therapy with 90 Y and 177 Lu for different volumes of the tumor using the criterion of self-absorbed dose, cross-absorbed dose, absorbed dose profile, absorbed dose uniformity, and dose-volume histogram (DVH) curve using Gate Monte Carlo simulation code., Material and Methods: In our analytical study, Gate Monte Carlo simulation code has been used to model tumors and simulate particle transport. Spherical tumors were modeled from radius 0.5 to 20 mm. Tumors were uniformly designed from water (soft tissue reagent). The full energy spectrum of each radionuclide of 177 Lu and 90 Y was used in the total volume of tumors with isotropic radiation, homogeneously. Self-absorbed dose, cross-absorbed dose, absorbed dose profile, absorbed dose uniformity, and DVH curve parameters were evaluated., Results: The absorbed dose for 90 Y is higher than 177 Lu in all tumors (p-value <5%). The uniformity of the absorbed dose for 177 Lu is much greater than 90 Y. As the tumor size increases, the DVH graph improves for 90 Y., Conclusion: Based on self-absorbed dose, cross-absorbed dose, absorbed dose uniformity, and DVH diagram, 177 Lu and 90 Y are appropriate for smaller and larger tumors, respectively. Next, we can evaluate the appropriate cocktail of these radionuclides, in terms of the type of composition, for the treatment of tumors with a specific size., Competing Interests: Conflict of Interest: None, (Copyright: © Journal of Biomedical Physics and Engineering.)