|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Evidence-based consensus on the diagnosis, prevention and management of hepatitis C virus disease显示文摘Hepatitis C virus(HCV) is a potent human pathogen and is one of the main causes of chronic hepatitis round the world. The present review describes the evidencebased consensus on the diagnosis, prevention and management of HCV disease. Various techniques, for the detection of anti-HCV immunoglobulin G immunoassays, detection of HCV RNA by identifying virus-specific molecules nucleic acid testings, recognition of core antigen for diagnosis of HCV, quantitative antigenassay, have been used to detect HCV RNA and core antigen. Advanced technologies such as nanoparticlebased diagnostic assays, loop-mediated isothermal amplification and aptamers and Ortho trak-C assay have also come to the front that provides best detection results with greater ease and specificity for detection of HCV. It is of immense importance to prevent this infection especially among the sexual partners, injecting drug users, mother-to-infant transmission of HCV, household contact, healthcare workers and people who get tattoos and piercing on their skin. Management of this infection is intended to eradicate it out of the body of patients. Management includes examining the treatment(efficacy and protection), assessment of hepatic condition before commencing therapy, controlling the parameters upon which dual and triple therapies work, monitoring the body after treatment and adjusting the co-factors. Examining the treatment in some special groups of people(HIV/HCV co-infected, hemodialysis patients, renal transplanted patients). | Mahrukh Akbar Shaheen Muhammad Idrees | 2015 | World Journal of Hepatology2015，7，3： | 9 |
| 2 | Carbon tetrachloride-induced nephrotoxicity in rats: Protective role of Digera muricata显示文摘 | Muhammad R. Khan Wajiha Rizvi Gul N. Khan Rahmat A. Khan Saima Shaheen | 2008 | Journal of Ethnopharmacology2008，，1： | 1 |
| 3 | Facile Synthesis as well as Structural, Raman, Dielectric and Antibacterial Characteristics of Cu Doped ZnO Nanoparticles显示文摘Here, undoped and Cu doped ZnO nanoparticles(NPs) have been prepared by chemical co-precipitation technique. X-ray diffraction(XRD) results reveal that Cu ions are successfully doped into ZnO matrix without altering its wurtzite phase. The single wurtzite phase of ZnO is retained even for 10 wt% Cu doped ZnO sample. It is observed from the electron microscopy results that higher level of Cu doping varies the morphology of ZnO NPs from spherical to flat NPs. Moreover, the particle size is found to increase with the increase in Cu doping level. Raman spectroscopy results further confirm that Cu dopant has not altered the wurtzite structure of ZnO. Impedance spectroscopy results reveal that the dielectric constant and dielectric loss have increasing trend with Cu doping. Cu doping has been found to slightly decrease the bactericidal potency of ZnO nanoparticles. | Javed Iqbal Nauman Safdar Tariq Jan Muhammad Ismail S.S.Hussain Arshad Mahmood Shaheen Shahzad Qaisar Mansoor | 2015 | Journal of Materials Science & Technology2015，31，3： | 1 |
| 4 | Data Mining Applications in Hydrocar- bon Exploration 显示文摘 | Muhammad Shaheen Muhammad Shahbaz Zahoor ur Rehman | 2011 | Artif Intell Rev2011，35，： | 1 |
| 5 | Functional Null Mutations of MSRB3 Encoding Methionine Sulfoxide Reductase Are Associated with Human Deafness DFNB74显示文摘 | Zubair M. Ahmed Rizwan Yousaf Byung Cheon Lee Shaheen N. Khan Sue Lee Kwanghyuk Lee Tayyab Husnain Atteeq Ur Rehman Sarah Bonneux Muhammad Ansar Wasim Ahmad Suzanne M. Leal Vadim N. Gladyshev Inna A. Belyantseva Guy Van Camp Sheikh Riazuddin Thomas B. Fri | 2011 | The American Journal of Human Genetics2011，，1： | 1 |
| 6 | Complete ^1H-NMR and ^13C-NMR assignments of stigma-5-en-3-O-β- glueoside and its acetyl derivative 显示文摘 | Shaheen F Muhammad A Rubeena S | 2001 | Magn Resonance Chem2001，39，： | 1 |
| 7 | Importance of Features Selection,Attributes Selection,Challenges and Future Directions for Medical Imaging Data:A Review显示文摘In the area of pattern recognition and machine learning,features play a key role in prediction.The famous applications of features are medical imaging,image classification,and name a few more.With the exponential growth of information investments in medical data repositories and health service provision,medical institutions are collecting large volumes of data.These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality.On the other hand,this growth also made it difficult to comprehend and utilize data for various purposes.The results of imaging data can become biased because of extraneous features present in larger datasets.Feature selection gives a chance to decrease the number of components in such large datasets.Through selection techniques,ousting the unimportant features and selecting a subset of components that produces prevalent characterization precision.The correct decision to find a good attribute produces a precise grouping model,which enhances learning pace and forecast control.This paper presents a review of feature selection techniques and attributes selection measures for medical imaging.This review is meant to describe feature selection techniques in a medical domainwith their pros and cons and to signify its application in imaging data and data mining algorithms.The review reveals the shortcomings of the existing feature and attributes selection techniques to multi-sourced data.Moreover,this review provides the importance of feature selection for correct classification of medical infections.In the end,critical analysis and future directions are provided. | Nazish Naheed Muhammad Shaheen Sajid Ali Khan Mohammed Alawairdhi Muhammad Attique Khan | 2020 | Computer Modeling in Engineering & Sciences2020，，10： | 1 |
| 8 | CARM:Context Based Association Rule Mining for Conventional Data显示文摘This paper is aimed to develop an algorithm for extracting association rules,called Context-Based Association Rule Mining algorithm(CARM),which can be regarded as an extension of the Context-Based Positive and Negative Association Rule Mining algorithm(CBPNARM).CBPNARM was developed to extract positive and negative association rules from Spatiotemporal(space-time)data only,while the proposed algorithm can be applied to both spatial and non-spatial data.The proposed algorithm is applied to the energy dataset to classify a country’s energy development by uncovering the enthralling interdependencies between the set of variables to get positive and negative associations.Many association rules related to sustainable energy development are extracted by the proposed algorithm that needs to be pruned by some pruning technique.The context,in this paper serves as a pruning measure to extract pertinent association rules from non-spatial data.Conditional Probability Increment Ratio(CPIR)is also added in the proposed algorithm that was not used in CBPNARM.The inclusion of the context variable and CPIR resulted in fewer rules and improved robustness and ease of use.Also,the extraction of a common negative frequent itemset in CARM is different from that of CBPNARM.The rules created by the proposed algorithm are more meaningful,significant,relevant and insightful.The accuracy of the proposed algorithm is compared with the Apriori,PNARM and CBPNARM algorithms.The results demonstrated enhanced accuracy,relevance and timeliness. | Muhammad Shaheen Umair Abdullah | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 9 | Indirect Vector Control of Linear Induction Motors Using Space Vector Pulse Width Modulation显示文摘Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications. | Arjmand Khaliq Syed Abdul Rahman Kashif Fahad Ahmad Muhammad Anwar Qaisar Shaheen Rizwan Akhtar Muhammad Arif Shah Abdelzahir Abdelmaboud | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 10 | Wild melon: a novel non-edible feedstock for bioenergy显示文摘In the present research work, a non-edible oil source Cucumis melo var. agrestis(wild melon) was systematically identified and studied for biodiesel production and its characterization. The extracted oil was 29.1% of total dry seed weight. The free fatty acid value of the oil was found to be 0.64%, and the single-step alkaline transesterification method was used for conversion of fatty acids into their respective methyl esters. The maximum conversion efficiency of fatty acids was obtained at 0.4 wt% Na OH(used as catalyst), 30%(methanol to oil, v/v) methanol amount, 60 ℃ reaction temperature,600-rpm agitation rate and 60-min reaction time. Under these optimal conditions, the conversion efficiency of fatty acid was 92%. However, in the case of KOH as catalyst, the highest conversion(85%) of fatty acids was obtained at 40%methanol to oil ratio, 1.28 wt% KOH, 60 ℃ reaction temperature, 600-rpm agitation rate and 45 min of reaction time.Qualitatively, biodiesel was characterized through Fourier transform infrared spectroscopy(FTIR) and gas chromatography and mass spectroscopy(GC–MS). FTIR results demonstrated a strong peak at 1742 cm^(-1), showing carbonyl groups(C=O)of methyl esters. However, GC–MS results showed the presence of twelve methyl esters comprised of lauric acid, myristic acid, palmitic acid, non-decanoic acid, hexadecanoic acid, octadecadienoic acid and octadecynoic acid. The fuel properties were found to fall within the range recommended by the international biodiesel standard, i.e., American Society of Testing Materials(ASTM): flash point of 91 ℃, density of 0.873 kg/L, viscosity of 5.35 c St, pour point of-13 ℃, cloud point of-10 ℃, total acid number of 0.242 mg KOH/g and sulfur content of 0.0043 wt%. The present work concluded the potential of wild melon seed oil as excellent non-edible source of bioenergy. | Maria Ameen Muhammad Zafar Mushtaq Ahmad Anjuman Shaheen Ghulam Yaseen | 2018 | Petroleum Science2018，15，2： | 0 |
| 11 | Optimized health care for subjects with type 1 diabetes in a resource constraint society: A three-year follow-up study from Pakistan显示文摘BACKGROUND Inadequate health infrastructure and poverty especially in rural areas are the main hindrance in the optimal management of subjects with type 1 diabetes (T1D) in Pakistan. AIM To observe effectiveness of diabetes care through development of model clinics for subjects with T1D in the province of Sindh Pakistan. METHODS A welfare project with name of “Insulin My Life”, was started in province of Sindh, Pakistan. This was collaborative work of Baqai Institute of Diabetology and Endocrinology, World Diabetes Foundation and Baqai Medical University between February 2010 to February 2013. Under this project thirty-four T1D clinics were established. Electronic database was designed for demographic, biochemical, anthropometric and medical examination. Monthly consultation was part of the standardized diabetes care. All the recruited subjects with T1D were provided free insulins and related materials. RESULTS Out of 1428 subjects, 795 (55.7%) were males and 633 (44.3%) were females. Subjects were categorized into ≤ 5 years of age 103 (7.2%), between 6-12 years 323 (22.6%), between 13–18 years 428 (29.7%) and ≥ 19 years of age 574 (40.2%) groups. Glycemic control as assessed by HbA1c was significantly improved (P <0.0001) at three years follow up as compared to baseline in all age groups. Decreasing trends of mean self-monitoring blood glucose were observed at different meal timings in all age groups. No significant change was found in the frequency of neuropathy, nephropathy and retinopathy during the study period (P > 0.05). CONCLUSION This study gives us long-term longitudinal data of people with T1D in a resource constraint society. With provision of standardized and comprehensive care significant improvement in glycemic control without any change in the frequency of microvascular complications was observed over 3 years. | Muhammad Yakoob Ahmedani Asher Fawwad Fariha Shaheen Bilal Tahir Nazish Waris Abdul Basit | 2019 | World Journal of Diabetes2019，10，3： | 0 |
| 12 | Epidemiological trends of mosquito-borne viral diseases in Pakistan显示文摘Globally,arboviruses are public health problems.Pakistan has seen a fast-paced increase in mosquito-borne Flavivirus diseases such as dengue because of deforestation,climate change,urbanization,poor sanitation and natural disasters.The magnitude and distribution of these diseases are poorly understood due to the lack of a competitive nationwide surveillance system.In dengue-endemic countries,the recent epidemics of chikungunya(CHIKV)and human West Nile virus(WNV)have created panic among the public and are thought to provoke an outbreak of Zika virus(ZIKV)in Pakistan.Recently,hospital-based surveillance has indicated the presence of Japanese encephalitis virus(JEV),which is deeply concerned by developing countries such as Pakistan.The situation could become more devastating because of poorly developed diagnostic infrastructure.To date,no licensed vaccine has been used in Pakistan,and preventive measures are mainly based on vector control.This review provides comprehensive information concerning the association of risk factors with disease occurrence,epidemiological trends,and prediction of the spread of mosquito-borne diseases,attention to new threats of ZIKV,and future perspectives by benchmarking global health policies. | Muhammad Imran Jing Ye Muhammad K.Saleemi Iqra Shaheen Ali Zohaib Zheng Chen Shengbo Cao | 2022 | Animal Diseases2022，2，2： | 0 |
| 13 | B^(2)C^(3)NetF^(2):Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection显示文摘Currently,the improvement in AI is mainly related to deep learning techniques that are employed for the classification,identification,and quantification of patterns in clinical images.The deep learning models show more remarkable performance than the traditional methods for medical image processing tasks,such as skin cancer,colorectal cancer,brain tumour,cardiac disease,Breast cancer(BrC),and a few more.The manual diagnosis of medical issues always requires an expert and is also expensive.Therefore,developing some computer diagnosis techniques based on deep learning is essential.Breast cancer is the most frequently diagnosed cancer in females with a rapidly growing percentage.It is estimated that patients with BrC will rise to 70%in the next 20 years.If diagnosed at a later stage,the survival rate of patients with BrC is shallow.Hence,early detection is essential,increasing the survival rate to 50%.A new framework for BrC classification is presented that utilises deep learning and feature optimization.The significant steps of the presented framework include(i)hybrid contrast enhancement of acquired images,(ii)data augmentation to facilitate better learning of the Convolutional Neural Network(CNN)model,(iii)a pre‐trained ResNet‐101 model is utilised and modified according to selected dataset classes,(iv)deep transfer learning based model training for feature extraction,(v)the fusion of features using the proposed highly corrected function‐controlled canonical correlation analysis approach,and(vi)optimal feature selection using the modified Satin Bowerbird Optimization controlled Newton Raphson algorithm that finally classified using 10 machine learning classifiers.The experiments of the proposed framework have been carried out using the most critical and publicly available dataset,such as CBISDDSM,and obtained the best accuracy of 94.5%along with improved computation time.The comparison depicts that the presented method surpasses the current state‐ofthe‐art approaches. | Mamuna Fatima Muhammad Attique Khan Saima Shaheen Nouf Abdullah Almujally Shui‐Hua Wang | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
| 14 | Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases显示文摘Machine Learning(ML)has changed clinical diagnostic procedures drastically.Especially in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human errors.Enormous studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical procedures.Multi-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical diagnostics.DL formulates reliable accuracy with big datasets but the reverse is the case with small datasets.This paper proposed a novel method that deals with the issue of less data dimensionality.Inspired by the regression analysis,the proposed method classifies the data by going through three different stages.In the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final classifications.Extensive experiments were carried out on the Cleveland heart disease dataset.The results show significant improvement in classification accuracy.It is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future. | Wasif Akbar Adbul Mannan Qaisar Shaheen Mohammad Hijji Muhammad Anwar Muhammad Ayaz | 2023 | Computers, Materials & Continua2023，，6： | 0 |
| 15 | Energy Cost Minimization Using String Matching Algorithm in Geo-Distributed Data Centers显示文摘Data centers are being distributed worldwide by cloud service providers(CSPs)to save energy costs through efficient workload alloca-tion strategies.Many CSPs are challenged by the significant rise in user demands due to their extensive energy consumption during workload pro-cessing.Numerous research studies have examined distinct operating cost mitigation techniques for geo-distributed data centers(DCs).However,oper-ating cost savings during workload processing,which also considers string-matching techniques in geo-distributed DCs,remains unexplored.In this research,we propose a novel string matching-based geographical load balanc-ing(SMGLB)technique to mitigate the operating cost of the geo-distributed DC.The primary goal of this study is to use a string-matching algorithm(i.e.,Boyer Moore)to compare the contents of incoming workloads to those of documents that have already been processed in a data center.A successful match prevents the global load balancer from sending the user’s request to a data center for processing and displaying the results of the previously processed workload to the user to save energy.On the contrary,if no match can be discovered,the global load balancer will allocate the incoming workload to a specific DC for processing considering variable energy prices,the number of active servers,on-site green energy,and traces of incoming workload.The results of numerical evaluations show that the SMGLB can minimize the operating expenses of the geo-distributed data centers more than the existing workload distribution techniques. | Muhammad Imran Khan Khalil Syed Adeel Ali Shah Izaz Ahmad Khan Mohammad Hijji Muhammad Shiraz Qaisar Shaheen | 2023 | Computers, Materials & Continua2023，，6： | 0 |
| 16 | 基于信息隐藏的RGB图像像素指示高容量技术显示文摘基于掩密图像而使用的图像称为掩护媒体。最低有效位(LSB)是在此领域常用的一种技术,个别使用图像内的LSB进行掩密的方案是可利用的。本文综合了随机像素操作方法和掩密密钥的思想指导研究工作,即使用其中一个通道的最低2bits来显示其他两个通道数据的存在。这项工作最终显示出许多值得关注的结果,尤其是与RGB图像像素有关的被隐藏的数据位的容量。 | Adnan Gutub Mahmoud Ankeer Muhammad Abu-Ghalioun Abdulrahman Shaheen Aleem Alvi 李娟 | 2009 | 中国印刷与包装研究2009，，5： | 0 |
| 17 | Outbreak of Crimean-Congo haemorrhagic fever with atypical clinical presentation in the Karak District of Khyber Pakhtunkhwa,Pakistan显示文摘Background:Crimean-Congo haemorrhagic fever(CCHF)is a potentially fatal disease endemic in Pakistan.The causative virus is transmitted by the bite of Hyalomma ticks or by contact with infected blood or tissue.First cases of the disease were reported in Pakistan in 1976 but regular outbreaks have been observed since the year 2000.A huge agricultural base with more than 175 million livestock,the concomitant presence of Hyalomma ticks and a lack of precautionary measures to prevent transmission lead to a considerable risk for exposed populations to contract CCHF in Pakistan.At the same time,secondary cases contracted by nosocomial transmission are reported from hospitals.Case presentation:Here we present an outbreak of CCHF with four of six patients succumbing to the disease before the suspicion for CCHF was raised.Importantly,the main clinical features of these cases were gastrointestinal symptoms without any clinical signs of bleeding.Only the last two patients in this outbreak presented with typical signs of bleeding disorder and were then confirmed being infected by CCHF.Confirmation of diagnosis was done at the National Institute of Health by real-time RT-PCR.Conclusions:This case series highlights the importance of early clinical suspicion for CCHF in exposed individuals and the need for improved precautionary measures against the spread of CCHF within the Pakistani population and hospitals. | Khalid Rehman Muhammad Asif Khan Bettani Luzia Veletzky Shaheen Afridi Michael Ramharter | 2018 | Infectious Diseases of Poverty2018，7，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员