Background: Tracheal sound analysis is a simple way to study the abnormalities of upper airway like airway obstruction. Hence, it may be an effective method for detection of alveolar hypoventilation and respiratory depression. This study was designed to investigate the importance of tracheal sound analysis to detect respiratory depression during cataract surgery under sedation. Methods: After Institutional Ethical Committee approval and informed patients' consent, we studied thirty adults American Society of Anesthesiologists I and II patients scheduled for cataract surgery under sedation anesthesia. Recording of tracheal sounds started 1 min before administration of sedative drugs using a microphone. Recorded sounds were examined by the anesthesiologist to detect periods of respiratory depression longer than 10 s. Then, tracheal sound signals converted to spectrogram images, and image processing was done to detect respiratory depression. Finally, depression periods detected from tracheal sound analysis were compared to the depression periods detected by the anesthesiologist. Results: We extracted five features from spectrogram images of tracheal sounds for the detection of respiratory depression. Then, decision tree and support vector machine (SVM) with Radial Basis Function (RBF) kernel were used to classify the data using these features, where the designed decision tree outperforms the SVM with a sensitivity of 89% and specificity of 97%. Conclusions: The results of this study show that morphological processing of spectrogram images of tracheal sound signals from a microphone placed over suprasternal notch may reliably provide an early warning of respiratory depression and the onset of airway obstruction in patients under sedation.

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Nowadays, magnetic resonance imaging (MRI) has a high ability to distinguish between soft tissues because of high spatial resolution. Image processing is extensively used to extract clinical data from imaging modalities. In the medical image processing field, the knee's cyst (especially Baker) segmentation is one of the novel research areas. There are different methods for image segmentation. In this paper, the mathematical operation of the watershed algorithm is utilized by MATLAB software based on marker-controlled watershed segmentation for the detection of Baker's cyst in the knee's joint MRI sagittal and axial T2-weighted images. The performance of this algorithm was investigated, and the results showed that in a short time Baker's cyst can be clearly extracted from original images in axial and sagittal planes. The marker-controlled watershed segmentation was able to detect Baker's cyst reliable and can save time and current cost, especially in the absence of specialists it can help us for the easier diagnosis of MRI pathologies.

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Biologic scaffolds composed of extracellular matrix (ECM) are frequently used for clinical purposes of tissue regeneration. Different methods have been developed for this purpose. All methods of decellularization including chemical and physical approaches leave some damage on the ECM; however, the effects of these methods are different which make some of these procedures more proper to maintain ECM structure than other methods. This review is aimed to introduce and compare new physical methods for the decellularization of different tissues and organs in tissue engineering. All recent reports and research that have used at least one physical method in the procedure of decellularization, were included and evaluated in this paper. The advantages and drawbacks of each method were examined and compared considering the effectiveness. This review tried to highlight the prospective potentials and benefits of applying physical methods for decellularization protocols in tissue engineering instead of the current chemical methods. These chemical methods are harsh in nature and were shown to be destructive and harmful to essential substances of ECM and scaffold structure. Therefore, using physical methods as a partial or even a whole protocol could save time, costs, and quality of the final acellular tissue in complicated decellularization procedures. Moreover, regarding the control factor that could be achieved easily with physical methods, optimization of different decellularization protocols would be quite satisfactory. Combined methods take advantage of both chemical and physical approaches.

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Novel drug delivery systems have ameliorated drugs' pharmacokinetics and declined undesired ramifications while led to a better patient compliance by extending the time of release. In fact, although there has been a multitude of encouraging achievements in controlled drug release, the application of micro- and nano-carriers is confronted with some challenges such as rapid clearance and inefficient targeting. In addition, since cell systems can be an appropriate alternative to micro- and nano-particles, they have been used as biological carriers. In general, features such as stable release into blood, slow clearance, efficient targeting, and high biocompatibility are the main properties of cells applied as drug carriers. Furthermore, some cells such as erythrocytes, leukocytes, stem cells, and platelets have been used as release systems. Hence, most common cells that were used as aforementioned release systems are going to be presented in this review article.

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Background: The increasing trend of heart disease has turned the attention of researchers toward the use of portable connected technologies. The necessity of continuous special care for cardiovascular patients is an inevitable fact. Methods: In this research, a new wireless electrocardiographic (ECG) signal-monitoring system based on smartphone is presented. This system has two main sections. The first section consists of a sensor which receives ECG signals via an amplifier, then filters and digitizes the signal, and prepares it to be transmitted. The signals are stored, processed, and then displayed in a mobile application. The application alarms in dangerous situations and sends the location of the cardiac patient to family or health-care staff. Results: The results obtained from the analysis of the electrocardiogram signals on 20 different people have been compared with the traditional ECG in hospital by a cardiologist. The signal is instantly transmitted by 200 sample per second to mobile phone. The raw data are processed, the anomaly is detected, and the signal is drawn on the interface in about 70 s. Therefore, the delay is not noticeable by the patient. With respect to rate of data transmission to hospital, different internet connections such as 2G, 3G, 4G, WiFi, WiMax, or Long-Term Evolution (LTE) could be used. Data transmission ranges from 9.6 kbps to 20 Mbps. Therefore, the physician could receive data with no delay. Conclusions: A performance accuracy of 91.62% is obtained from the wireless ECG system. It conforms to the hospital’s diagnostic standard system while providing a portable monitoring anywhere at anytime.

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Background: The tracking devices could help measuring the heart rate and energy expenditure and recognizing the user's activity. The calorie measurement is a significant achievement for the fitness tracking and the continuous health monitoring. Methods: In this paper, a combination of an accelerometer and a photoplethysmography (PPG) sensor is implemented to calculate the calories consumed. These sensors were mounted next to each other and then were placed on the ankle and finger by flat cable. The sensed data are transferred via Bluetooth to a smartphone in a serial and real-time manner. An Android App is designed to display the user's health data. The average amount of consumed energy is obtained from the combination of the accelerometer sensor based on the laws of motion and the PPG sensor based on the heart rate data. Results: The designed system is tested on 10 nonathlete males and 10 nonathlete females randomly. By applying thevelet, the value of the acceleration signal variance was reduced from 3.2 to 0.8. The correlation between PPG and pulse oximeter was 0.9. Moreover, the correlation of the accelerometer and treadmill was 0.9. The root mean square error (RMSE) and the P value of the calorie output from PPG and pulse oximeter are 0.53 and 0.008, respectively. The RMSE and the P value of the calories output from the accelerometer and the treadmill are 0.42 and 0.007, respectively. Conclusion: Our device validity and reliability were good by comparing it with a typical smart band, smart watch, and smartphone available in the market. The combined PPG and the accelerometer sensors were compared with the gold standard, the pulse oximeter, and the treadmill. According to the results, there is no significant difference in the values obtained. Therefore, a mobile system is augmented with the wireless accelerometer and PPG that are connected to a smartphone. The system could be carried out with the user at any time and any place.

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Bromelain is dotted with anticancer properties on various cancer cell lines. Anticancer pathways of bromelain, as well related intervening signalization are under investigation. Investigating the inhibitory potential of bromelain on AGS, PC3, and MCF7 cells proliferation and colony formation. The bromelain inhibitory potential on AGS, PC3, and MCF7 cells proliferation at various bromelain concentrations was assessed by MTT; thereby, bromelain potency on colony formation impediment was evaluated using clonogenic assays at determined 50% inhibitory concentrations (IC₅₀) on four different cell densities (10, 50, 100, and 200 cells per well). Bromelain inhibits AGS, PC3, and MCF7 cells proliferation in such a dose-dependent manner. Determined IC₅₀to AGS, PC3, and MCF7 cells were 65, 60 and 65μg/ml respectively. At IC₅₀, bromelain significantly suppressed the AGS, PC3, and MCF7 cells colony formation at four treated densities (10, 50, 100 and 200 cells per well). Plating efficiency percentage and cell surviving fraction were decreased after bromelain treatment to AGS, PC3, and MCF7 human cancer cells as a function of initial cell density. The 50, 50 or 100, and 10 or 50 cells per well were considered to be optimum number of initial cell density for AGS, PC3, and MCF7 cells. Cell proliferative and colony formation inhibition are two pathways to in vitro bromelain anticancer effects. The current study displayed a dose-dependent inhibitory effect of bromelain, as well impeding colony formation AGS, PC3, and MCF7 human cancer cells.

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Background: Breast cancer is one of the most common cancers in women. Mammogram images have an important role in the treatment of various states of this cancer. In recent years, machine learning methods have been widely used for tumor segmentation in mammogram images. Pixel-based segmentation methods have been presented using both supervised and unsupervised learning approaches. Supervised learning methods are usually fast and accurate, but they usually use a large number of labeled data. Besides, providing these samples is very hard and usually expensive. Unsupervised learning methods do not require the labels of the training data for decision making and they completely ignore the prior knowledge that may lead to a low performance. Semi-supervised learning methods which use a small number of labeled data solve the problem of providing the high number of samples in supervised methods, while they usually result in a higher accuracy in comparison to the unsupervised methods. Methods: In this study, we used a semisupervised method for tumor segmentation in which the pixel information is used for the classification. The static and gray level run length matrix features for each pixel are considered as the features, and Fisher discriminant analysis (FDA) is used for feature reduction. A cotraining algorithm based on support vector machine and Bayes classifiers is proposed for tumor segmentation on MIAS data set. Results and Conclusion: The results show that the proposed method outperforms both supervised methods.

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Background: Relative to classical methods in computed tomography, iterative reconstruction techniques enable significantly improved image qualities and/or lowered patient doses. However, the computational speed is a major concern for these iterative techniques. In the present study, we present a method for fast system matrix calculation based on the line integral model (LIM) to speed up the computations without compromising the image quality. In addition, we develop a hybrid line–area integral model (AIM) that highlights the advantages of both LIM and AIMs. Methods: The contributing detectors for a given pixel and a given projection view, and the length of corresponding intersection lines with pixels, are calculated using our proposed algorithm. For the hybrid method, the respective narrow-angle fan beam was modeled by multiple equally spaced lines. The computed system matrix was evaluated in the context of reconstruction using the simultaneous algebraic reconstruction technique (SART) as well as maximum likelihood expectation maximization (MLEM). Results: The proposed LIM offers a considerable reduction in calculation times compared to the standard Siddon algorithm: 2.9 times faster. Differences in root mean square error and peak signal-to-noise ratio were not significant between the proposed LIM and the Siddon algorithm for both SART and MLEM reconstruction methods (P > 0.05). Meanwhile, the proposed hybrid method resulted in significantly improved image qualities relative to LIM and the Siddon algorithm (P < 0.05), though computations were 4.9 times more intensive than the proposed LIM. Conclusion: We have proposed two fast algorithms to calculate the system matrix. The first is based on LIM and was faster than the Siddon algorithm, with matched image quality, whereas the second method is a hybrid LIM–AIM that achieves significantly improved images though with its computational requirements.

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Background: People with diabetes need to monitor their blood sugar levels constantly and attend health centers regularly for checkups. The aim of this study is to provide a healthcare system for mobile blood glucose and bilirubin monitoring. Methods: It includes a sensor for noninvasive blood glucose and bilirubin measurement using near-infrared spectroscopy and optical method, respectively, communicating with a smartphone. Results: It was observed that by increasing the glucose concentration, the output voltage of the sensor increases in transmittance mode and decreases in reflectance mode. Moreover, it was observed that by increasing the bilirubin concentration, the output voltage of sensor decreases in transmittance mode and increases in reflectance mode. In the collected data there was good correlations between voltage and concentration and their relationship were approximately linear. Therefore, it is possible to use noninvasive methods to predict the glucose or bilirubin concentration. In vivo experiments for glucose were carried out with 19 persons in training phase, and five persons were used for testing the model. The glucose behavior model was built into the mobile application. The average glucose concentrations from the transmittance and reflectance mode were obtained. The average percentage error was 8.27 and root mean square error was 18.52 mg/dL. Conclusions: From this research, it can be inferred that the noninvasive optical methods implemented on wireless sensors and smartphones could form a system that can be used at any time and any place in the future as an alternative to traditional invasive blood glucose and bilirubin measurement methods.

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Individuals with psychophysiological insomnia (Psych-Insomnia) would show raised cortical arousal through their initiating sleep. Frequent changes in the alpha activity can be indicative of visual cortical activation, even without visual stimulation or retinal input. Therefore, we aimed to investigate alpha-wave characteristics in Psych-Insomnia before and after sleep onset. In a case–control study, 11 individuals with Psych-Insomnia (age: 44.00 ± 13.27) and 11 age-, sex-, and body mass index-matched healthy individuals (age: 41.64 ± 15.89) were recruited for this study. An overnight polysomnography monitoring was performed. Alpha characteristics were calculated from wake before sleep onsets (WBSOs), wake after sleep onset, rapid eye movement, and nonrapid eye movement in the both groups. They include the alpha power and alpha frequency and their variability in the central region. In the WBSO, alpha activity and variability were higher in the Psych-Insomnia individuals compared to healthy individuals. In both groups, alpha frequency variability was observed at approximately 1 Hz. Alpha-wave synchronization in Psych-Insomnia individuals was higher than the group with normal sleep. Individuals with Psych-Insomnia have a lot of imagination in the wake before sleep, which can be caused by stress, everyday concerns, and daily concerns.

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Background: The severe acute respiratory syndrome-like disease coronavirus disease 2019 (COVID-19) is a disastrous global pandemic with 16,288,490 infected cases and 649,884 deaths. Until now, no effective treatments are found. Methods: The virus uses the 3-chymotrypsin-like protease for inducing the activity of the viral polyproteins and the spike (S) glycoprotein for human cell entry through the human angiotensin-converting enzyme 2 receptor. Blocking the active binding sites of these molecules might be beneficial for decreasing the activity of the virus and suppressing the viral entry to the human cells. Here, docking methods were used to identify a group of ligands may perform the blocking operations. Results: The results revealed the strongest binding affinities, sorted high to low, for tadalafil (Cialis) (phosphodiesterase type 5 inhibitor, tirofiban (antiplatelet), paraxanthine (central nervous system stimulant), dexamethasone, gentian violet cation (triphenylmethane), salbutamol, and amlodipine (calcium channel blocker). Conclusion: These substances may provide vital help for further clinical investigation in fighting against the current global pandemic of the COVID-19.

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Background: Decellularization techniques have been widely used in tissue engineering recently. However, applying these methods which are based on removing cells and maintaining the extracellular matrix (ECM) encountered some difficulties for dense tissues such as articular cartilage. Together with chemical agents, using physical methods is suggested to help decellularization of tissues. Methods: In this study, to improve decellularization of articular cartilage, the effects of direct and indirect ultrasonic waves as a physical method in addition to sodium dodecyl sulfate (SDS) as chemical agents with 0.1% and 1% (w/v) concentrations were examined. Decellularization process was evaluated by nucleus staining with hematoxylin and eosin (H and E) and by staining glycosaminoglycans (GAG) and collagen. Results: The H and E staining indicated that 1% (w/v) SDS in addition to ultrasonic bath for 5 h significantly decreased the cell nucleus residue to lacuna ratio by 66%. Scanning electron microscopy showed that using direct sonication caused formation of micropores on the surface of the sample which results in better penetration of decellularization material and better cell attachment after decellularization. Alcian Blue and Picrosirius Red staining represented GAG and collagen, respectively, which maintained in ECM structure after decellularization by ultrasonic bath and direct sonicator. Conclusion: Ultrasonic bath can help better penetration of the decellularization material into the cartilage. This improves the speed of the decellularization process while it has no significant defect on the structure of the tissue.

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Background: Gas sensor array system is a device that mimics the work of how the nose smells using the gas sensors that could give response toward specific odors. It is used for characterizing the different blended gas that is suited with the biological working nose principle. Thus, it could be used to detect the dental and oral diseases. Periodontitis is one of the diseases caused by the damage on the teeth due to the chronic infection on the gingival structure marked with bacterial plaque and calculus. This study aims to develop an electric nose for odor detection application on the periodontal bacterial biofilm as early detection device for dental and oral disease. Methods: This device is designed as a portable device to ease the data acquisition. The measured data were stored at a database system connected to a real-time computer. A gas array sensor system with six gas sensors (TGS 826, TGS 2602, TGS 2600, TGS 2611, TGS 2612, and TGS 2620) has been assembled for the early detection application for dental and oral disease excreted by the bacterial biofilm that caused dental and oral disease, including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Streptococcus mutans, and Enterococcus faecalis. Results: TGS 826 and TGS 2602 sensor had the best response showed by the high ADC delta value. Conclusion: GS 826 and TGS 2602 sensor could be used as a candidate for early detection device for dental and oral disease.

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Background: Parkinson's disease (PD) is the most common destructive neurological disorder after Alzheimer's disease. Unfortunately, there is no specific test such as electroencephalography or blood test for diagnosing the disease. In accordance with the previous studies, about 90% of people with PD have some types of voice abnormalities. Therefore, voice measurements can be used to detect the disease. Methods: This study presents an ensemble-based method for identifying patients and healthy samples by class label prediction based on voice frequency characteristics. It includes three stages of data preprocessing, internal classification and ultimate classification. The outcomes of internal classifiers next to primary feature vector of samples are considered the ultimate classifier inputs. Results: According to the results, the proposed method achieved 90.6% of accuracy, 95.8% of sensitivity, and 75% of specificity, admissible compared to those of other relevant studies. Conclusion: Current experimental outcomes provide a comparative analysis of various machine learning classifiers and confirm that using ensemble-based methods has improved medical diagnostic tasks.

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Background: Automatic vehicle location (AVL) refers to a system that calculates the geographical location of any vehicle, i.e., latitude and longitude. Vehicle location information about one or more moving vehicles can be stored in the internal memory and accessed when vehicles are available (offline tracking). It is also possible to get location information on a real-time basis (online tracking). The real-time tracking systems designed to date may incorporate three devices: global positioning system (GPS), geographic information system, and cellular communication platforms that may be either a general packet radio service (GPRS) or any private and local radiofrequency network. Methods: The GPS-based navigation system has been designed so as to allow for user-friendly real-time tracking applications for any emergency vehicles like ambulances. First, GPS coordinates are obtained from the SIM908 module and sent via to a server transmission control protocol/internet protocol. Server codes, which are written in C#, load Google map to show real-time location. Results: We designed online tracking AVL hardware in the two simple and advanced versions. The latter enables both the ambulance driver and the data center to monitor path real-time besides enabling the vehicle driver to receive and make calls and send or receive messages. The former only sends latitude and longitude to the data server continuously, and the path travelled by vehicle is displayed. Conclusion: SIM908 integrates GSM, GPRS, and GPS in one package. It can be a proper choice for real-time economic tracking systems despite its low accuracy in finding geolocations.

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Nowadays, it is obvious that there is a relationship between changes in the retinal vessel structure and diseases such as diabetic, hypertension, stroke, and the other cardiovascular diseases in adults as well as retinopathy of prematurity in infants. Retinal fundus images provide non-invasive visualization of the retinal vessel structure. Applying image processing techniques in the study of digital color fundus photographs and analyzing their vasculature is a reliable approach for early diagnosis of the aforementioned diseases. Reduction in the arteriolar–venular ratio of retina is one of the primary signs of hypertension, diabetic, and cardiovascular diseases which can be calculated by analyzing the fundus images. To achieve a precise measuring of this parameter and meaningful diagnostic results, accurate classification of arteries and veins is necessary. Classification of vessels in fundus images faces with some challenges that make it difficult. In this paper, a comprehensive study of the proposed methods for classification of arteries and veins in fundus images is presented. Considering that these methods are evaluated on different datasets and use different evaluation criteria, it is not possible to conduct a fair comparison of their performance. Therefore, we evaluate the classification methods from modeling perspective. This analysis reveals that most of the proposed approaches have focused on statistics, and geometric models in spatial domain and transform domain models have received less attention. This could suggest the possibility of using transform models, especially data adaptive ones, for modeling of the fundus images in future classification approaches.

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Background: Asymmetry analysis of retinal layers in right and left eyes can be a valuable tool for early diagnoses of retinal diseases. To determine the limits of the normal interocular asymmetry in retinal layers around macula, thickness measurements are obtained with optical coherence tomography (OCT). Methods: For this purpose, after segmentation of intraretinal layer in threedimensional OCT data and calculating the midmacular point, the TM of each layer is obtained in 9 sectors in concentric circles around the macula. To compare corresponding sectors in the right and left eyes, the TMs of the left and right images are registered by alignment of retinal raphe (i.e. diskfovea axes). Since the retinal raphe of macular OCTs is not calculable due to limited region size, the TMs are registered by first aligning corresponding retinal raphe of fundus images and then registration of the OCTs to aligned fundus images. To analyze the asymmetry in each retinal layer, the mean and standard deviation of thickness in 9 sectors of 11 layers are calculated in 50 normal individuals. Results: The results demonstrate that some sectors of retinal layers have signifcant asymmetry with P < 0.05 in normal population. In this base, the tolerance limits for normal individuals are calculated. Conclusion: This article shows that normal population does not have identical retinal information in both eyes, and without considering this reality, normal asymmetry in information gathered from both eyes might be interpreted as retinal disorders.

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Electro encephalography (EEG) is one of the most reliable sources to detect sleep onset while driving. In this study, we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. So, first of all, we have recorded EEG signals from 10 volunteers. They were obliged to avoid sleeping for about 20 hours before the test. We recorded the signals while subjects did a virtual driving game. They tried to pass some barriers that were shown on monitor. Process of recording was ended after 45 minutes. Then, after preprocessing of recorded signals, we labeled them by drowsiness and alertness by using times associated with pass times of the barriers or crash times to them. Then, we extracted some chaotic features (include Higuchi's fractal dimension and Petrosian's fractal dimension) and logarithm of energy of signal. By applying the two-tailed t-test, we have shown that these features can create 95% significance level of difference between drowsiness and alertness in each EEG channels. Ability of each feature has been evaluated by artificial neural network and accuracy of classification with all features was about 83.3% and this accuracy has been obtained without performing any optimization process on classifier.

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Background: Nowadays, the role of smart systems and developed tools such as wearable systems for monitoring the patients and controlling their conditions consistently has increased significantly. The present research sought to identify the factors which are essential for designing a wearable smart blanket system and modeling the proposed systems. Methods: To this aim, the requirements for creating the proposed system in ambulance were described after determining the features related to wearable systems by conducting on a comparative study. First, some studies were performed to identify the wearable system development. Then, the elicited questionnaire was given to the physicians and medical informatics specialists. Finally, the extracted requirements were implemented for modeling a smart blanket system. Results: Based on the results, the wearable smart blanket system includes some specific characteristics such as monitoring the important signs, communicating with the surroundings, processing the signals instantly, and storing all important signs. In addition, they should involve some nonfunctional characteristics such as easy installment and function, interactivity, error fault tolerance, low energy consumption, and the accuracy of sign stability. Then, based on the requirements and data elements extracted from the questionnaire, the system was modeled as a detailed design of the proposed technical blanket system. Based on the results, the architecture of the designed system could provide expected scenarios by using the Active Review for Intermediate Design-oriented scenario-based evaluation method. Conclusion: Today, smart systems and tools have considerably developed in terms of monitoring the patients and controlling their conditions. Therefore, wearable systems can be implemented for monitoring the health status of patients in ambulance.

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Background: Biopolymer scaffolds have received great interest in academic and industrial environment because of their supreme characteristics like biological, mechanical, chemical, and cost saving in the biomedical science. There are various attempts for incorporation of biopolymers with cheap natural micro- or nanoparticles like lignin (Lig), alginate, and gums to prepare new materials with enhanced properties. Methods: In this work, the electrospinning (ELS) technique as a promising cost-effective method for producing polymeric scaffold fibers was used, which mimics extracellular matrix structure for soft tissue engineering applications. Nanocomposites of Lig and polycaprolactone (PCL) scaffold produced with ELS technique. Nanocomposite containings (0, 5, 10, and 15 wt.%) of Lig were prepared with addition of Lig powder into the PCL solution while stirring at the room temperature. The bioactivity, swelling properties, morphological and mechanical tests were conducted for all the samples to investigate the nanocomposite scaffold features. Results: The results showed that scaffold with 10 wt.% Lig have appropriate porosity, biodegradation, minimum fiber diameter, optimum pore size as well as enhanced tensile strength, and young modulus compared with pure PCL. Degradation test performed through immersion of samples in the phosphate-buffer saline showed that degradation of PCL nanocomposites could accelerate up to 10% due to the addition of Lig. Conclusions: Electrospun PCL-Lig scaffold enhanced the biological response of the cells with the mechanical signals. The prepared nanocomposite scaffold can choose for potential candidate in the biomedical science.

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Background: Headache is one of the most common forms of medical complaints with numerous underlying causes and many patterns of presentation. The first step for starting the treatment is the recognition stage. In this article, the problem of primary and secondary headache diagnosis is considered, and we evaluate the use of intelligence techniques and soft computing in order to predict the diagnosis of common headaches. Methods: A fuzzy expert-based system for the diagnosis of common headaches by Learning-From-Examples (LFE) algorithm is presented, in which Mamdani model was used in fuzzy inference engine using Max–Min as Or–And operators, and the Centroid method was used as defuzzification technique. In addition, this article has analyzed common headache using two classification techniques, and headache diagnosis based on a support vector machine (SVM) and multilayer perceptron (MLP)-based method has been proposed. The classifiers were used to recognize the four types of common headache, namely migraine, tension, headaches as a result of infection, and headaches as a result of increased intra cranial presser. Results: By using a dataset obtained from 190 patients, suffering from primary and secondary headaches, who were enrolled from a medical center located in Mashhad, the diagnostic fuzzy system was trained by LFE algorithm, and on an average, 123 pieces of If-Then rules were produced for fuzzy system, and it was observed that the system had the ability of correct recognition by a rate of 85%. Using the headache diagnostic system by MLP- and SVM-based decision support system, the accuracy of classification into four types improved by 88% when using the MLP and by 90% with the SVM classifier. The performance of all methods is evaluated using classification accuracy, precision, sensitivity, and specificity. Conclusion: As the linguistic rules may be incomplete when human experts express their knowledge, and according to the proximity of common headache symptoms and importance of early diagnosis, the LFE training algorithm is more effective than human expert system. Favorable results obtained by the implementation and evaluation of the suggested medical decision support system based on the MLP and SVM show that intelligence techniques can be very useful for the recognition of common headaches with similar symptoms.

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Despite the considerable improvement of the common-mode rejection ratio of digital filtering techniques, the electrocardiogram (ECG) traces recorded by commercialized devices are still contaminated by residual power line interference (PLI). In this study, we address this issue by proposing a novel real-time filter adapted to single-frequency noise cancellation and automatic power line frequency detection. The filtering process is principally based on a point-by-point fast Fourier transform and a judicious choice of the analysis window length. Intensive experiments conducted on real and synthetic signals have shown that our filtering method offers very clean ECGs, due to the suppression of spikes corresponding to the PLI and the preservation of spikes outside the filter band. In addition, this method is characterized by its low computational complexity which makes it suitable for real-time cleaning of ECG signals and thus can serve for more accurate diagnosis in computer-based automated cardiac system.

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Background: Radiotherapy is a main method for the treatment of breast cancer. This study aimed to measure the absorbed dose of thyroid gland using Gafchromic EBT2 film during breast cancer radiotherapy. In addition, the relationship between the absorbed dose and thyroid hormone levels was evaluated. Methods: Forty-six breast cancer patients, with the age ranged between 25 and 35 years, undergoing external radiotherapy were studied. The patients were treated with 6 and 18 MV X-ray beams, and the absorbed thyroid dose was measured by EBT2 film. Thyroid hormone levels, thyroid-stimulating hormone (TSH), triiodothyronine (T3), and thyroxin (T4), were measured before and after the radiotherapy. Pearson's, Spearman's, and Chi-square tests were performed to evaluate the correlation between the thyroid dose and hormone levels. Results: The mean thyroid dose was 26 ± 9.45 cGy with the range of 7.85–48.35 cGy. There were not any significant differences at thyroid hormone levels between preradiotherapy and postradiotherapy (P > 0.05). There was a significant relationship between increased thyroid absorbed dose and changes in TSH and T4 levels (P < 0.05), but it was not significant in T3 level (P = 0.1). Conclusion: Regarding the results, the thyroid absorbed dose can have an effect on its function. Therefore, the thyroid gland should be considered as an organ at risk in breast cancer radiotherapy.

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Background: The versatility of digital photographs and vast usage of image processing tools have made the image manipulation accessible and ubiquitous. Thus, there is an urgent need to develop digital image forensics tools, specifically for joint photographic experts group (JPEG) format which is the most prevailing format for storing digital photographs. Existing double JPEG methods needs improvement to reduce their sensitivity to the random grid shifts which is highly common in manipulation scenario. Also, a fully automatic pipeline, in terms of segmentation followed by the classifier is still required. Methods: First, a low-pass filter (with some modifications) is used to distinguish between high-textured and low-textured areas. Then, using the inconsistency values between the quality-factors, a grayscale image, called the ghost image, is constituted. To automate the whole method, a novel segmentation method is also proposed, which extracts the ghost borders. In the last step of the proposed method, using Kolmogorov–Smirnov statistic, the distance between two separated areas (ghost area and the rest of the image) is calculated and compared with a predefined threshold to confirm the presence of forgery/authenticity. Results: In this study, a simple yet efficient algorithm to detect double-JPEG compression is proposed. This method reveals the sub-visual differences in the quality factor in the different parts of the image. Afterward, forgery borders are extracted and are used to assess authenticity score. In our experiments, the average specificity of our segmentation method exceeds 92% and the average precision is 75%. Conclusion: The final binary results for classification are compared with six state-of-the-art methods. According to several performance metrics, our method outperforms the previously proposed ones.

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