Ocular manifestations of graft-versus-host disease

AbstractAllogeneic hematopoietic stem cell transplantation (HSCT) has evolved over the past two decades to become the standard of care for hematologic and lymphoid malignancies. Major ocular complications after allogeneic HSCT have been increasing in number and severity. Graft-versus-host disease (GVHD) remains a major cause of ocular morbidity after allogeneic HSCT. The main objective of this review is to elucidate the ocular complications in patients developing GVHD following HSCT.Ocular complications secondary to GVHD are common and include dry eye syndrome, acquisition of ocular allergy from donors with allergic disorders. Eyelid changes may occur in GVHD leading to scleroderma-like changes. Patients may develop poliosis, madarosis, vitiligo, lagophthalmos, and entropion. The cornea may show filamentary keratitis, superficial punctate keratitis, corneal ulcers, and peripheral corneal melting which may lead to perforation in severe cases. Scleritis may also occur which can be anterior or posterior. Keratoconjunctivis sicca appears to be the most common presentation of GVHD. The lacrimal glands may be involved with mononuclear cell infiltration of both the major and accessory lacrimal glands and decrease in tear production.Severe dry eye syndrome in patients with GVHD may develop conjunctival scarring, keratinization, and cicatrization of the conjunctiva.Therapy of GVHD includes systemic immunosuppression and local therapy. Surgical treatment in refractory cases includes surgical intervention to improve the manifestation of GVHD of the eye. This may include tarsorrhapy, prose lenses, punctal occlusions and corneal transplantation

Aspects of Islam and social coexistence: the case of Britain

This study deals with coexistence between Muslims and non-Muslims in the British society in the social context from an Islamic perspective. It identifies factors working for achieving coexistence between Muslims and non-Muslims in Britain. It also deals with factors that could undermine that coexistence. Then, it proposes certain ways for overcoming or, at least, reducing these factors. The study conducts a critical analytical reading of relevant studies and uncovers their defects. It then presents an operational definition of coexistence. This is helpful in designing the questionnaires' statements and analyzing their results. The questionnaires are structured around four main areas, namely cultural and social; values and traditions; living together; and finally behaviour and relationships. By tapping into these areas it is hoped that the research will be able to understand many prevailing social phenomena and identify the cultural and religious backgrounds, as well as the customs and traditions which interpret these phenomena. The questionnaires' have been subjected to scientific statistical analysis that helps to interpret the social phenomenon under study. In addition, a descriptive analytical methodology has been adopted to achieve integration between the statistical method and sociological approach in analyzing this phenomenon. The study reviews the uses of statistics in the Islamic experience and theoretical aspects of the statistical criteria. It show s how questionnaires' results were reached and examines their significance regarding representation of the sample's community. In conclusion, we have arrived at a number of alternative forms of Muslims' integration in order to achieve peaceful coexistence between the non-Muslims and the Muslims of the United Kingdom. We have also focused on Muslims' view on integration and its various alternatives and coexistence mechanisms, which we have divided into cognitive mechanisms concerning the activation of social studies in British universities and practical mechanisms in social reality on the levels of individuals and civil society organizations. The present study proposes several research criteria for future studies to be based on issues and problems of coexistence between Muslims and non-Muslims in Britain

Wireless body area sensor networks signal processing and communication framework: Survey on sensing, communication technologies, delivery and feedback

Problem statement: The Wireless Body Area Sensor Networks (WBASNs) is a wireless network used for communication among sensor nodes operating on or inside the human body in order to monitor vital body parameters and movements.This study surveys the state-of-the-art on Wireless Body Area Networks, discussing the major components of research in this area including physiological sensing and preprocessing, WBASNs communication techniques and data fusion for gathering data from sensors.In addition, data analysis and feedback will be presented including feature extraction, detection and classification of human related phenomena.Approach: Comparative studies of the technologies and techniques used in such systems will be provided in this study, using qualitative comparisons and use case analysis to give insight on potential uses for different techniques.Results and Conclusion: Wireless Sensor Networks (WSNs) technologies are considered as one of the key of the research areas in computer science and healthcare application industries.Sensor supply chain and communication technologies used within the system and power consumption therein, depend largely on the use case and the characteristics of the application.Authors conclude that Life-saving applications and thorough studies and tests should be conducted before WBANs can be widely applied to humans, particularly to address the challenges related to robust techniques for detection and classification to increase the accuracy and hence the confidence of applying such techniques without physician intervention

Survey on wireless body area sensor networks for healthcare applications: Signal processing, data analysis and feedback

Wireless sensor networks (WSNs) technologies are considered as one of the key of the research areas in computer science and healthcare application industries.The wireless body area sensor networks (WBASNs) is a wireless network used for communication among sensor nodes operating on or inside the human body in order to monitor vital body parameters and movements.The paper surveys the state-of-the-art on WBASNs discussing the major components of research in this area including physiological sensing, data preprocessing, detection and classification of human related phenomena. We provide comparative studies of the technologies and techniques used in such systems

Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data

Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study different brain activities.This study investigates the use of a new ensemble classifier to detect an epileptic seizure from compressed and noisy EEG signals. This noise-aware signal combination (NSC) ensemble classifier combines four classification models based on their individual performance. The main objective of the proposed classifier is to enhance the classification accuracy in the presence of noisy and incomplete information while preserving a reasonable amount of complexity.The experimental results show the effectiveness of the NSC technique, which yields higher accuracies of 90% for noiseless data compared with 85%, 85.9%, and 89.5% in other experiments. The accuracy for the proposed method is 80% when SNR = 1dB, 84% when SNR = 5dB, and 88% when SNR = 10dB, while the compression ratio (CR) is 85.35% for all of the datasets mentioned.NPRP 7-684-1-127, from the Qatar National Research Fund, a member of Qatar Foundation

Comparative Analysis of Data Mining Tools and Classification Techniques using WEKA in Medical Bioinformatics

The availability of huge amounts of data resulted in great need of data mining technique in order to generate useful knowledge. In the present study we provide detailed information about data mining techniques with more focus on classification techniques as one important supervised learning technique. We also discuss WEKA software as a tool of choice to perform classification analysis for different kinds of available data. A detailed methodology is provided to facilitate utilizing the software by a wide range of users. The main features of WEKA are 49 data preprocessing tools, 76 classification/regression algorithms, 8 clustering algorithms, 3 algorithms for finding association rules, 15 attribute/subset evaluators plus 10 search algorithms for feature selection. WEKA extracts useful information from data and enables a suitable algorithm for generating an accurate predictive model from it to be identified.  Moreover, medical bioinformatics analyses have been performed to illustrate the usage of WEKA in the diagnosis of Leukemia. Keywords: Data mining, WEKA, Bioinformatics, Knowledge discovery, Gene Expression

A Novel Deep Learning Strategy for Classifying Different Attack Patterns for Deep Brain Implants

Deep brain stimulators (DBSs), a widely used and comprehensively acknowledged restorative methodology, are a type of implantable medical device which uses electrical stimulation to treat neurological disorders. These devices are widely used to treat diseases such as Parkinson, movement disorder, epilepsy, and psychiatric disorders. Security in such devices plays a vital role since it can directly affect the mental, emotional, and physical state of human bodies. In worst-case situations, it can even lead to the patient's death. An adversary in such devices, for instance, can inhibit the normal functionality of the brain by introducing fake stimulation inside the human brain. Nonetheless, the adversary can impair the motor functions, alter impulse control, induce pain, or even modify the emotional pattern of the patient by giving fake stimulations through DBSs. This paper presents a deep learning methodology to predict different attack stimulations in DBSs. The proposed work uses long short-term memory, a type of recurrent network for forecasting and predicting rest tremor velocity. (A type of characteristic observed to evaluate the intensity of the neurological diseases) The prediction helps in diagnosing fake versus genuine stimulations. The effect of deep brain stimulation was tested on Parkinson tremor patients. The proposed methodology was able to detect different types of emulated attack patterns efficiently and thereby notifying the patient about the possible attack. - 2013 IEEE.This work was supported by the Qatar National Research Fund (a member of Qatar Foundation) through NPRP under Grant 8-408-2-172.Scopu

Acute spontaneous spinal subdural hematoma: A case report

BACKGROUND: Spontaneous spinal subdural hematoma is a rare condition that can lead to devastating neurologic deficits, usually caused by coagulation abnormalities, trauma, underlying neoplasm, or arteriovenous malformation. The patient presents with local and/or radicular pain, followed by loss of sensory, motor, bladder, and bowel function. CASE REPORT: A 25-year-old patient presented with left-sided weakness preceded by nontraumatic upper back pain. He denied any past medical illness and being on any regular medications. He had decreased strength in the left lower limb, left upper limb, and right lower limb, with intact strength in the right upper limb. The patient exhibited decreased sensation of pain and touch on the right side of the lower limb, bilateral loss of proprioception, and intact reflexes and anal tone. He had weakness on the left side of the body and contralateral decreased sensation of pain and touch on the right side. These symptoms were suggestive of Brown-Séquard syndrome, while the bilateral loss of proprioception suggested posterior cord syndrome. Magnetic resonance imaging showed an acute spinal subdural canal hematoma producing cord compression. The patient had an urgent laminectomy and hematoma evacuation. Afterward, his neurological function improved. CONCLUSIONS: Spontaneous spinal subdural hematoma can occur without any known pathology or remarkable trauma. It can compress the spinal cord and produce cerebral stroke-like symptoms. Hence, spinal hematoma should be ruled out in any patient presenting with a neurological deficit.Scopu

Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks

Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders

SURVEY ON WIRELESS BODY AREA SENSOR NETWORKS FOR HEALTHCARE APPLICATIONS: SIGNAL PROCESSING, DATA ANALYSIS AND FEEDBACK

ABSTRACT. Wireless sensor networks (WSNs) technologies are considered as one of the key of the research areas in computer science and healthcare application industries. The wireless body area sensor networks (WBASNs) is a wireless network used for communication among sensor nodes operating on or inside the human body in order to monitor vital body parameters and movements. The paper surveys the state-of-the-art on WBASNs discussing the major components of research in this area including physiological sensing, data preprocessing, detection and classification of human related phenomena. We provide comparative studies of the technologies and techniques used in such systems