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| 1 | Order selection in fractional Fourier transform based beamforming显示文摘Traditionally,beamforming using fractional Fourier transform(FrFT) involves a trial-and-error based FrFT order selection which is impractical.A new numerical order selection scheme is presented based on fractional power spectra(FrFT moment) of the linear chirp signal.This method can adaptively determine the optimum FrFT order by maximizing the second-order central FrFT moment.This makes the desired chirp signal substantially concentrated whereas the noise is rejected considerably.This improves the mean square error minimization beamformer by reducing effectively the signal-noise cross terms due to the finite data length de-correlation operation.Simulation results show that the new method works well under a wide range of signal to noise ratio and signal to interference ratio. | Muhammad Ishtiaq Ahmad | 2010 | Journal of Systems Engineering and Electronics2010，21，3： | 5 |
| 2 | Splenic injuries secondary to colonoscopy:Rare but serious complication显示文摘BACKGROUND Colonoscopy is a safe and routine diagnostic and therapeutic procedure for evaluation of large bowel diseases.Most common procedure related complications include bleeding and perforation but rarely a splenic Injury.AIM To investigate the reason for colonoscopy,presentation of patient with spleen injury,types of injury,diagnosis,management and outcomes of patients METHODS A structured search on four databases was done and 45 articles with 68 patients were selected.The reason for colonoscopy,presentation of patient with spleen injury,types of injury,diagnosis,management and outcomes of patients were identified and analyzed using SPSS.RESULTS The mean age of the patients was 62.7 years with 64%females.Twenty two percent had a complete splenic rupture with colonoscopy while 63%had subcapsular hematoma,spleen laceration and spleen avulsion.The most common reason for colonoscopy was screening(46%)followed by diagnostic colonoscopy(28%).Eighty seven percent of patients presented with abdominal pain.Patients with spleen rupture mostly required splenectomy(47%),while minor spleen hematomas and lacerations were managed conservatively(38%).Six percent of the patients were managed with proximal splenic artery splenic embolization and 4%were managed with laparoscopic repair.The overall mortality was 10%while 77%had complete recovery.The reason of colonoscopy against presentation specifically,abdominal pain showed no statistical significance P=0.69.The indication of colonoscopy had no significant impact on incidence of splenic injury(P=0.89).Majority of the patients(47%)were managed with splenectomy while the rest were managed conservatively(P=0.04).This association was moderately strong at a cramer’s V test(0.34).The Fisher exact test showed a higher mortality with spleen rupture(P=0.028).CONCLUSION Spleen rupture due to colonoscopy is a significant concern and is associated with high mortality.The management of the patients can be individualized based on clinical presentation. | Waqas Ullah Mamoon Ur Rashid Asif Mehmood Yousaf Zafar Ishtiaq Hussain Deepika Sarvepalli Muhammad Khalid Hasan | 2020 | World Journal of Gastrointestinal Surgery2020，12，2： | 4 |
| 3 | Additional Glycosylation Within a Specific Hypervariable Region of Subtype 3a of Hepatitis C Virus Protects Against Virus Neutralization显示文摘 | Sadia Anjum Ahmed Wahid Muhammad Sohail Afzal Anna Albecka Khaled Alsaleh Tahir Ahmad Thomas F. Baumert Czeslaw Wychowski Ishtiaq Qadri Fran?ois Penin Jean Dubuisson | 2013 | Journal of Infectious Diseases2013，，11： | 1 |
| 4 | COVID-19 and comorbidities of hepatic diseases in a global perspective显示文摘The worldwide outbreak of coronavirus disease 2019(COVID-19) has challenged the priorities of healthcare system in terms of different clinical management and infection transmission, particularly those related to hepatic-disease comorbidities. Epidemiological data evidenced that COVID-19 patients with altered liver function because of hepatitis infection and cholestasis have an adverse prognosis and experience worse health outcomes. COVID-19-associated liver injury is correlated with various liver diseases following a severe acute respiratory syndrome-coronavirus type 2(SARS-CoV-2) infection that can progress during the treatment of COVID-19 patients with or without pre-existing liver disease. SARS-CoV-2 can induce liver injury in a number of ways including direct cytopathic effect of the virus on cholangiocytes/hepatocytes, immune-mediated damage, hypoxia, and sepsis. Indeed, immediate cytopathogenic effects of SARSCoV-2 via its potential target, the angiotensin-converting enzyme-2 receptor, which is highly expressed in hepatocytes and cholangiocytes, renders the liver as an extra-respiratory organ with increased susceptibility to pathological outcomes. But, underlying COVID-19-linked liver disease pathogenesis with abnormal liver function tests(LFTs) is incompletely understood. Hence, we collated COVID-19-associated liver injuries with increased LFTs at the nexus of pre-existing liver diseases and COVID-19, and defining a plausible pathophysiological triad of COVID-19, hepatocellular damage, and liver disease. This review summarizes recent findings of the exacerbating role of COVID-19 in pre-existing liver disease and vice versa as well as international guidelines of clinical care, management, and treatment recommendations for COVID-19 patients with liver disease. | Aqsa Ahmad Syeda Momna Ishtiaq Junaid Ali Khan Rizwan Aslam Sultan Ali Muhammad Imran Arshad | 2021 | World Journal of Gastroenterology2021，27，13： | 1 |
| 5 | Biomarkers for virus-induced hepatocellular carcinoma (HCC)显示文摘 | Shilu Mathew Ashraf Ali Hany Abdel-Hafiz Kaneez Fatima Mohd Suhail Govindaraju Archunan Nargis Begum Syed Jahangir Muhammad Ilyas Adeel G.A. Chaudhary Mohammad Al Qahtani Salem Mohamad Bazarah Ishtiaq Qadri | 2014 | Infection, Genetics and Evolution2014，，： | 1 |
| 6 | Design of Latency-Aware IoT Modules in Heterogeneous Fog-Cloud Computing Networks显示文摘The modern paradigm of the Internet of Things(IoT)has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud computing.However,such applications cannot meet strict quality of service(QoS)requirements.The large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big data.Generally,cloud-centric IoT application deployment involves different modules running on terminal devices and cloud servers.Fog devices with different computing capabilities must process the data generated by the end device,so deploying latency-sensitive applications in a heterogeneous fog computing environment is a difficult task.In addition,when there is an inconsistent connection delay between the fog and the terminal device,the deployment of such applications becomes more complicated.In this article,we propose an algorithm that can effectively place application modules on network nodes while considering connection delay,processing power,and sensing data volume.Compared with traditional cloud computing deployment,we conducted simulations in iFogSim to confirm the effectiveness of the algorithm.The simulation results verify the effectiveness of the proposed algorithm in terms of end-to-end delay and network consumption.Therein,latency and execution time is insensitive to the number of sensors. | Syed Rizwan Hassan Ishtiaq Ahmad Jamel Nebhen Ateeq Ur Rehman Muhammad Shafiq Jin-Ghoo Choi | 2022 | Computers, Materials & Continua2022，，3： | 1 |
| 7 | Extraction of DNA suitable for PCR applications from mature leaves of Mangifera indica L.显示文摘Good quality deoxyribonucleic acid (DNA) is the pre-requisite for its downstream applications. The presence of high concentrations of polysaccharides, polyphenols, proteins, and other secondary me- tabolites in mango leaves poses problem in getting good quality DNA fit for polymerase chain reaction (PCR) applications. The problem is exacerbated when DNA is extracted from mature mango leaves. A reliable and modified protocol based on the cetyl- trimethylammonium bromide (CTAB) method for DNA extraction from mature mango leaves is described here. High concentrations of inert salt were used to remove polysaccharides; Polyvinylpyrrolidone (PVP) and β-mercaptoethanol were employed to manage phenolic compounds. Extended chloroform-isoamyl alcohol treatment followed by RNase treatment yielded 950?1050 μg of good quality DNA, free of protein and RNA. The problems of DNA degradation,contamination, and low yield due to irreversible binding of phenolic compounds and coprecipitation of polysaccharides with DNA were avoided by this method. The DNA isolated by the modified method showed good PCR amplification using simple se- quence repeat (SSR) primers. This modified protocol can also be used to extract DNA from other woody plants having similar problems. | Muhammad Abubakkar AZMAT Iqrar Ahmad KHAN Hafiza Masooma Naseer CHEEMA Ishtiaq Ahmad RAJWANA Ahmad Sattar KHAN Asif Ali KHAN | 2012 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2012，13，4： | 1 |
| 8 | Unordered rule discovery using Ant Colony Optimization显示文摘In this article,a novel unordered classification rule list discovery algorithm is presented based on Ant Colony Optimization(ACO).The proposed classifier is compared empirically with two other ACO-based classification techniques on 26 data sets,selected from miscellaneous domains,based on several performance measures.As opposed to its ancestors,our technique has the flexibility of generating a list of IF-THEN rules with unrestricted order.It makes the generated classification model more comprehensible and easily interpretable.The results indicate that the performance of the proposed method is statistically significantly better as compared with previous versions of AntMiner based on predictive accuracy and comprehensibility of the classification model. | KHAN Salabat BAIG Abdul Rauf ALI Armughan HAIDER Bilal KHAN Farman Ali DURRANI Mehr Yahya ISHTIAQ Muhammad | 2014 | Science China(Information Sciences)2014，57，9： | 1 |
| 9 | Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature Selection显示文摘As big data,its technologies,and application continue to advance,the Smart Grid(SG)has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology(ICT)and cloud computing.As a result of the complicated architecture of cloud computing,the distinctive working of advanced metering infrastructures(AMI),and the use of sensitive data,it has become challenging tomake the SG secure.Faults of the SG are categorized into two main categories,Technical Losses(TLs)and Non-Technical Losses(NTLs).Hardware failure,communication issues,ohmic losses,and energy burnout during transmission and propagation of energy are TLs.NTL’s are human-induced errors for malicious purposes such as attacking sensitive data and electricity theft,along with tampering with AMI for bill reduction by fraudulent customers.This research proposes a data-driven methodology based on principles of computational intelligence as well as big data analysis to identify fraudulent customers based on their load profile.In our proposed methodology,a hybrid Genetic Algorithm and Support Vector Machine(GA-SVM)model has been used to extract the relevant subset of feature data from a large and unsupervised public smart grid project dataset in London,UK,for theft detection.A subset of 26 out of 71 features is obtained with a classification accuracy of 96.6%,compared to studies conducted on small and limited datasets. | Muhammad Umair Zafar Saeed Faisal Saeed Hiba Ishtiaq Muhammad Zubair Hala Abdel Hameed | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 10 | Comparison of Wheat Planting Methods and Residue Incorporation Under Saline-Sodic Soil显示文摘 | Muhammad Arshadullah Massomma Hassan Arshad Ali Syed Ishtiaq Hyder | 2011 | Journal of Life Sciences2011，5，12： | 0 |
| 11 | 无次要路径主动噪声控制系统的生物启发式与内点混合法(英文)显示文摘开发了一种主动噪声控制(active noise control,ANC)系统的混合计算框架,运用基于遗传算法(geneticalgorithm,GA)和内点法(interior-point method,IPM)的进化计算技术,集成得到GA-IPM方法。标准ANC系统通常采用滤波扩展最小均方算法优化线性有限脉冲响应滤波器的系数,但易陷入局部极小值(local minima,LM)。本文提出的GA-IPM计算方法有效解决了上述问题。该法不易出现LM问题,且无需识别方案中ANC系统的次级路径。采用正弦、随机和复杂随机噪声干扰下的耳机ANC模型,对该方法在几种线性和非线性主级和次级路径状况下的表现进行评估。大量独立运行算法的统计分析结果验证了该方案的准确性和收敛性。 | Muhammad Asif Zahoor RAJA Muhammad Saeed ASLAM Naveed Ishtiaq CHAUDHARY Wasim Ullah KHAN | 2018 | Frontiers of Information Technology & Electronic Engineering2018，19，2： | 0 |
| 12 | Flower Pollination Heuristics for Nonlinear Active Noise Control Systems显示文摘In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems. | Wasim Ullah Khan Yigang He Muhammad Asif Zahoor Raja Naveed Ishtiaq Chaudhary Zeshan Aslam Khan Syed Muslim Shah | 2021 | Computers, Materials & Continua2021，，4： | 0 |
| 13 | 一例慢性乙肝患者甲胎蛋白检测结果的差异所带来的挑战显示文摘Introduction Alpha-fetoprotein(AFP)is the most abundant serum protein found in the human fetus,produced by the yolk sac and the liver[1].The levels of maternal serum AFP reach a peak value at28-32 weeks of gestation and decrease rapidly after birth and usually drop to the normal at 8-12 months of age.The normal serum AFP level for an adult is<20 ng/mL[2].In contrast,livertumor cells usually synthesize and secrete an increased level of AFP.Abdominal ultrasound and AFP are generally recommended as the screening modality for HCC for patients at risk for development of hepatocellular carcinoma(HCC)[1].AFP-L3,an isoform of AFP that binds Lens culinaris agglutinin,can be particularly useful in the early identification of aggressive HCC[2].These assays,however,can generate false-positive and false-negative AFP values.Of patients with advanced HCC,20%had normal AFP levels,whereas some patients with liver diseases had significant AFP elevation without liver cancer in long-term surveillance[3].Elevated AFP levels could be associated with active liver diseases with hepatocyte regeneration[4,5].In that setting,the AFP level will decline with improvement of the underlying liver condition.Our case illustrated the dilemma and uncertainties as a result of persistent abnormal AFP values after extensive clinical investigations. | Pir A.Shah Allison Onken Rizwan Ishtiaq Muhammad H.Maqsood Shyam S.Patel Karen J.Campoverde Reyes Adrianna Z.Herskovits Daryl T.Y.Lau | 2020 | Gastroenterology Report2020，8，6： | 0 |
| 14 | On the stacking fault forming probability and stacking fault energy in carbon-doped 17 at%Mn steels via transmission electron microscopy and atom probe tomography显示文摘Assessing the stacking fault forming probability(P_(sf)) and stacking fault energy(SFE)in medium-or highMn base structural materials can anticipate and elucidate the microstructural evolution before and after deformation.Typically,these two parameters have been determined from theoretical calculations and empirical results.However,the estimation of SFE values in Fe–Mn–C ternary systems is a longstanding debate due to the complicated nature of carbon:that is,whether the carbon doping indeed plays an important role in the formation of stacking faults;and how the amount of carbon atoms exist at grain boundaries or at internal grains with respect to the nominal carbon doping contents.Herein,the use of atom probe tomography and transmission electron microscopy(TEM)unveils the influence of carbondoping contents on the structural properties of dual-phase Fe–17 Mn–x C(x=0–1.56 at%)steels,such as carbon segregation free energy at grain boundaries,carbon concentration in grain interior,interplanar D-spacings,and mean width of intrinsic stacking faults,which are essential for SFE estimation.We next determined the Psfvalues by two different methods,viz.,reciprocal-space electron diffraction measurements and stacking fault width measurements in real-space TEM images.Then,SFEs in the Fe–17 Mn–x C systems were calculated on the basis of the generally-known SFE equations.We found that the high amount of carbon doping gives rise to the increased SFE from 8.6 to 13.5 m J/m^(2)with non-linear variation.This SFE trend varies inversely with the mean width of localized stacking faults,which pass through both other stacking faults and pre-existingε-martensite plates without much difficulty at their intersecting zones.The high amount of carbon doping acts twofold,through increasing the segregation free energy(due to more carbon at grain boundaries)and large lattice expansion(due to increased soluble carbon at internal grains).The experimental data obtained here strengthens the composition-dependent SFE maps for predicting the deformation structure and mechanical response of other carbon-doped high-Mn alloy compositions. | Hyo Ju Bae Kwang Kyu Ko Muhammad Ishtiaq Jung Gi Kim Hyokyung Sung Jae Bok Seol | 2022 | Journal of Materials Science & Technology2022，，20： | 0 |
| 15 | Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya显示文摘The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure. | Hamza DAUD Javed Iqbal TANOLI Sardar Muhammad ASIF Muhammad QASIM Muhammad ALI Junaid KHAN Zahid Imran BHATTI Ishtiaq Ahmad Khan JADOON | 2024 | Journal of Mountain Science2024，21，1： | 0 |
| 16 | Cyclic beamforming using fractional Fourier transform domain cyclostationarity显示文摘 | Muhammad Ishtiaq Ahmad Liu Zhiwen Xu Yougen | 2011 | High Technology Letters2011，17，1： | 0 |
| 17 | Physicochemical,rheological and antioxidant profiling of yogurt prepared from non-enzymatically and enzymatically hydrolyzed potato powder under refrigeration显示文摘Evidences show that the storage period greatly affects the quality of yogurt.In this study,three types of yogurt:control yogurt(CY),non-hydrolyzed potato powder yogurt(PPY)and enzymatically hydrolyzed potato powder yogurt(EHPPY)were prepared at 42℃ for 5 h and stored for 28 days at 4℃.The yogurts were evaluated for quality characteristics at different storage periods.Negligible differences in pH values,titratable acidities and viable counts were detected in all three types of yogurt during storage.However,compared to other yogurts,EHPPY exhibited desirable water holding capacity,throughout the storage period.Apart from this,sensory properties and antioxidant activities(2-diphenyl-1-picryl-hydrazyl(DPPH)free radical scavenging activity and ferric reducing antioxidant power(FRAP))of EHPPY were also significantly improved during the storage period.Furthermore,the storage(G’)and loss(G”)modulus of PPY,EHPPY were lower than CY at 4℃ while a hysteresis loop was shown by all yogurts at the temperature range of 4-50℃ indicating higher G’(elasticity)than G”(viscosity).Based on our findings,EHPP could be an important functional ingredient in improving the quality and storage stability of yogurt for its production at an industrial level. | Ishtiaq Ahmad Zhouyi Xiong Hanguo Xiong Rana Muhammad Aadil Nauman Khalid Allah Bakash Jvaid Lakhoo Zia-ud-din Asad Nawaz Noman Walayat Rao Sanaullah Khan | 2023 | Food Science and Human Wellness2023，12，1： | 0 |
| 18 | Flower Pollination Heuristics for Parameter Estimation of Electromagnetic Plane Waves显示文摘For the last few decades,the parameter estimation of electromagnetic plane waves i.e.,far field sources,impinging on antenna array geometries has attracted a lot of researchers due to their use in radar,sonar and under water acoustic environments.In this work,nature inspired heuristics based on the flower pollination algorithm(FPA)is designed for the estimation problem of amplitude and direction of arrival of far field sources impinging on uniform linear array(ULA).Using the approximation in mean squared error sense,a fitness function of the problem is developed and the strength of the FPA is utilized for optimization of the cost function representing scenarios for various number of sources non-coherent located in the far field.The worth of the proposed FPA based nature inspired computing heuristic is established through assessment studies on fitness,histograms,cumulative distribution function and box plots analysis.The other worthy perks of the proposed scheme include simplicity of concept,ease in the implementation,extendibility and wide range of applicability to solve complex optimization problems.These salient features make the proposed approach as an attractive alternative to be exploited for solving different parameter estimation problems arising in nonlinear systems,power signal modelling,image processing and fault diagnosis. | Sadiq Akbar Muhammad Asif Zahoor Raja Naveed Ishtiaq Chaudhary Fawad Zaman Hani Alquhayz | 2021 | Computers, Materials & Continua2021，，8： | 0 |
| 19 | Performance Evaluation of Virtualization Methodologies to Facilitate NFV Deployment显示文摘The development of the Next-Generation Wireless Network(NGWN)is becoming a reality.To conduct specialized processes more,rapid network deployment has become essential.Methodologies like Network Function Virtualization(NFV),Software-Defined Networks(SDN),and cloud computing will be crucial in addressing various challenges that 5G networks will face,particularly adaptability,scalability,and reliability.The motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms,including hypervisors,clouds,and containers,which will serve as a guide to dealing with the stimulating environment of 5G.This is particularly crucial when implementing network operations at the edge of 5G networks,where limited resources and prompt user responses are mandatory.Experimental results prove that containers outperform hypervisor-based virtualized infrastructure and cloud platforms’latency and network throughput at the expense of higher virtualized processor use.In contrast to public clouds,where a set of rules is created to allow only the appropriate traffic,security is still a problem with containers. | Sumbal Zahoor Ishtiaq Ahmad Ateeq Ur Rehman Elsayed Tag Eldin Nivin AGhamry Muhammad Shafiq | 2023 | Computers, Materials & Continua2023，，4： | 0 |
| 20 | Reinforcing Artificial Neural Networks through Traditional Machine Learning Algorithms for Robust Classification of Cancer显示文摘Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target values.However,improving predictive accuracy is a crucial step for informed decision-making.In the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or diagnosis.Among ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification tasks.The network weights and the activation functions are the two crucial elements in the learning process of an ANN.These weights affect the prediction ability and the convergence efficiency of the network.In traditional settings,ANNs assign random weights to the inputs.This research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random weights.The proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer classification.This system computes the confusion matrix-based metrics for traditional and proposed frameworks.The proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other models.The results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research limitations.Moreover,the proposed framework is of use to predict and classify cancer patients accurately.Consequently,this will facilitate the effective management of cancer patients. | Muhammad Hammad Waseem Malik Sajjad Ahmed Nadeem Ishtiaq Rasool Khan Seong-O-Shim Wajid Aziz Usman Habib | 2023 | Computers, Materials & Continua2023，，5： | 0 |
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