检索结果-南通市图书馆

Risk of hepatocellular carcinoma after hepatitis C virus cure

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Gastroenterology 2022年第1期28卷 96-107页

作者： Maria Alejandra Luna-Cuadros Hao-Wei Chen Hira Hanif Mukarram Jamat Ali muzammil muhammad khan Daryl Tan-Yeung Lau Liver Center Division of Gastroenterology and Hepatology Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMA 02215United States

Hepatitis C virus(HCV)is a significant cause of hepatocellular carcinoma(HCC).The direct-acting antivirals marked a new era of HCV therapy and are associated with greater than 95%cure rate.Successful treatment of chronic hepatitis C greatly reduces the risk of HCC.A proportion of patients,especially those with pre-existing cirrhosis,remain at risk for HCC despite sustained virologic response(SVR).Diabetes mellitus,hepatic steatosis,alcohol consumption and lack of fibrosis regression are associated with risks of HCC after HCV cure.Noninvasive modalities such as aspartate aminotransferase to platelet ratio index and fibrosis-4 index and transient elastography have been used to monitor hepatic fibrosis.More recently,various fibrosis scores have been combined with clinical parameters and other novel biomarkers to predict risks of HCC for patients who achieved SVR.These models still need to be validated and standardized prior to applying to routine clinical care.

关键词： Hepatitis C virus cure Hepatocellular carcinoma Hepatocellular carcinoma risk models Fibrosis markers Transient elastography

Deep Learning Based Classification of Wrist Cracks from X-ray Imaging

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第10期73卷 1827-1844页

作者： Jahangir Jabbar muzammil Hussain Hassaan Malik Abdullah Gani Ali Haider khan muhammad Shiraz Department of Computer Science National College of Business Administration&Economics LahoreMultan60000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Faculty of Computing and Informatics University of Malaysia SabahJalan UMSKota Kinabalu88400SabahMalaysia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabadPakistan

Wrist cracks are the most common sort of cracks with an excessive occurrence rate.For the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented by crack depiction.Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping.Indeed,many hospitals lack experienced clinicians to diagnose wrist cracks.Therefore,an automated system is required to reduce the burden on clinicians and identify cracks.In this study,we have designed a novel residual network-based convolutional neural network(CNN)for the crack detection of the wrist.For the classification of wrist cracks medical imaging,the diagnostics accuracy of the RN-21CNN model is compared with four well-known transfer learning(TL)models such as Inception V3,Vgg16,ResNet-50,and Vgg19,to assist the medical imaging technologist in identifying the cracks that occur due to wrist fractures.The RN-21CNN model achieved an accuracy of 0.97 which is much better than its competitor`s approaches.The results reveal that implementing a correct generalization that a computer-aided recognition system precisely designed for the assistance of clinician would limit the number of incorrect diagnoses and also saves a lot of time.

关键词： Wrist cracks fracture deep learning X-rays CNN

Energy and Life Cycle Assessment of Zinc/Water Nanofluid Based Photovoltaic Thermal System

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy Engineering 2022年第2期119卷 827-846页

作者： Junaid khan Rashid Ali muzammil Zubair Syed Mohd Yahya SEARL Laboratory Department of Mechancial EngineeringAligarh Muslim UniversityAligarh202002India

Cooling the PV surface in a Photovoltaic Thermal system is a pivotal operational aspect to be taken into account to achieve optimized values of performance parameters in a Photovoltaic Thermal System.The experimental design used in this study facilitates the flow of varying concentrations of Zn-water nanofluid in serpentine copper tubing installed at the rear of the PV panel thereby preventing the PV surface temperature from increasing beyond the threshold value at which a decrease in electrical efficiency starts to occur.This fusion of solar thermal with PV devices leads to better electrical and thermal efficiency values resulting in decreased cell degradation over time and maximization of the lifespan of the PV module and the energy output from the PV system.Due to the superior thermal heat properties of nanofluids,their usage in such systems has become increasingly widespread.Life cycle metrics which include Energy Payback period,Energy Production Factor and life cycle conversion efficiency were evaluated for the PVT system by exhaustively chalking fundamental parameters such as embodied energy of the PVT setup and the total energy output from the PVT system.This research aims to be a major milestone in the evolutionary journey of Photovoltaic Thermal modules by guiding the engineers working on the theory,design and implementation of PVT systems towards its economic feasibility,environmental impact and energy sustainability.

关键词： Photovoltaic thermal system nanofluids performance parameters life cycle assessment

The dilemma of cytomegalovirus and hepatitis B virus interaction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Gastroenterology Report 2022年第1期10卷 108-114页

作者： muzammil M.khan Mukarram J.Ali Hira Hanif muhammad H.Maqsood Imama Ahmad Javier E.G.Alvarez Maria-Andreea Catana Daryl T.Y.Lau Department of Medicine Division of GastroenterologyLiver Research CenterBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMAUSA Department of Medicine North Shore Medical CenterSalemMAUSA

Hepatitis B virus(HBV)remains a global public health problem despite the availability of effective vaccine and antiviral therapy.Cytomegalovirus(CMV),another hepatotropic virus,is also very prevalent in the general population worldwide.Both HBV and CMV can persist in the host and have potential to reactivate especially with weakened host cellular immunity.Superimposed CMV infection can lead to severe HBV reactivation.The pathogenesis of the co-infection of HBV and CMV remains poorly understood.Studies reported conflicting results regarding the inhibitory effect of CMV on HBV replication.There is an unmet need on the management of co-infection of HBV and CMV;research initiatives dedicated to understanding their interactions are urgently needed.

关键词： CMV HBV HBV CMV co-infection CMV reactivation HBV reactivation IgG Avidity test

Sentiment Analysis Based on Performance of Linear Support Vector Machine and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal on Big Data 2023年第1期5卷 1-18页

作者： Mian muhammad Danyal Sarwar Shah khan muzammil khan muhammad Bilal Ghaffar Bilal khan muhammad Arshad Department of Computer Science City University of Science&TechnologyPeshawar25000Pakistan Department of Computer Science and Software Technology University of SwatSwat19200Pakistan Department of Computer Software Engineering University of Engineering&Technology MardanMardan23200Pakistan Department of Computer Science IQRA National UniversitySwat19200Pakistan

Movies are the better source of entertainment.Every year,a great percentage of movies are released.People comment on movies in the form of reviews after watching them.Since it is difficult to read all of the reviews for a movie,summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews.Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data.Opinion mining involves identifying and extracting the opinions of individuals,which can be positive,neutral,or negative.The task of opinion mining also called sentiment analysis is performed to understand people’s emotions and attitudes in movie reviews.Movie reviews are an important source of opinion data because they provide insight into the general public’s opinions about a particular movie.The summary of all reviews can give a general idea about the movie.This study compares baseline techniques,Logistic Regression,Random Forest Classifier,Decision Tree,K-Nearest Neighbor,Gradient Boosting Classifier,and Passive Aggressive Classifier with Linear Support Vector Machines and Multinomial Naïve Bayes on the IMDB Dataset of 50K reviews and Sentiment Polarity Dataset Version 2.0.Before applying these classifiers,in pre-processing both datasets are cleaned,duplicate data is dropped and chat words are treated for better results.On the IMDB Dataset of 50K reviews,Linear Support Vector Machines achieve the highest accuracy of 89.48%,and after hyperparameter tuning,the Passive Aggressive Classifier achieves the highest accuracy of 90.27%,while Multinomial Nave Bayes achieves the highest accuracy of 70.69%and 71.04%after hyperparameter tuning on the Sentiment Polarity Dataset Version 2.0.This study highlights the importance of sentiment analysis as a tool for understanding the emotions and attitudes in movie reviews and predicts the performance of a movie based on the average sentiment of all the reviews.

关键词： Opinion mining machine learning movie reviews IMDB Dataset of 50K reviews Sentiment Polarity Dataset Version 2.0

Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第7期76卷 133-150页

作者： Ali Haider khan Hassaan Malik Wajeeha Khalil Sayyid Kamran Hussain Tayyaba Anees muzammil Hussain Department of Software Engineering Faculty of Computer SciencesLahore Garrison UniversityLahorePakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Computer Science&Information Technology University of Engineering and Technology(UET)PeshawarPakistan Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated immediately.Color fundus imaging(CFI)is a screening technology that is both effective and economical.According to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic algorithms.The traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of eyes.In addition,they usually only target one or a few different kinds of eye diseases at the same time.In this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs classification.PLML_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification scores.The DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right CFI.After then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel basis.After the attributes have been analyzed,they are integrated to provide a representation at the patient level.Throughout the whole process of ODs categorization,the patient-level representation will be used.The efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

关键词： Ocular disease multi-label spatial correlation CNN eye disease

Inhibitive efficacy of Nymphoides indica rhizome extract onα-glucosidase, and cross-link formation of advanced glycation end products

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Traditional Chinese Medicine 2021年第3期41卷 376-380页

作者： muhammad Hanif muzammil Ahmad khan muhammad Ramzan Abdul Rafey Ali Zaman Imran Aziz Ama'null'ah Adnan Amin Gomal Centre of Biochemistry and Biotechnology(GCBB) Gomal University D.I.Khan29050Pakistan NPRL Department of PharmacognosyFaculty of PharmacyGomal University D.I.Khan29050Pakistan FVAS Gomal University D.I.Khan29050Pakistan

OBJECTIVE: To investigate the inhibitive efficacy of Nymphoides Indica(L.) Kuntze rhizome extract onα-glucosidase and on cross-link formation of advanced glycation end products(AGEs).METHODS: The plant extracts were prepared by cold maceration and fractionated in solvents of diverse polarity. The in vitro α-glucosidase inhibition assay, fluorescence spectrometry and SDS-PAGE analysis was performed for antiglycation assays.RESULTS: During α-glucosidase inhibition assay significant inhibition by chloroform(0.43 mg/mL)and methanol fractions(0.66 mg/mL) was noticed.During the AGEs inhibition assay, both oxidative(BSA-MGO) and non-oxidative(BSA-glucose)modes were employed. The inhibition of AGEs by total extract was considered moderate(IC_(50)0.10 mg/mL) as a result of non-oxidative mode, whereas in case of oxidative mode(BASA-MGO) no activity was recorded. Among fractions the methanolic fraction presented significant results both in oxidative(IC_(50)0.01 mg/mL) and non-oxidative modes(IC_(50) 0.3 mg/mL). Likewise the ethyl acetate fraction was more active in non-oxidative mode(IC_(50)0.04 mg/mL) compared to oxidative mode(IC_(50)0.32 mg/mL).During assay for inhibition of cross-link formation,the chloroform fraction significantly inhibited cross-link formation in a dose dependent mode.CONCLUSION: It was finally concluded that N. Indica rhizome extract possesses significant properties that inhibit α-glucosidase, and AGEs cross-link formation.

关键词： Nymphoides Indica alpha-glucosidases glycation end products advanced protein cross links antiglycation

Migraine in physicians and final year medical students:A crosssectional insight into prevalence,self-awareness,and knowledge from Pakistan

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

World Journal of Methodology 2022年第5期12卷 414-427页

作者： Hassan Choudry Fateen Ata muhammad Naveed Naveed Alam Ruqaiya Ruqaiya Mahammed khan Suheb muhammad Qaiser Ikram muhammad muzammil Chouhdry Muaz Muaz Department of Respiratory Medicine University Hospital of LeicesterLeicester LE1United Kingdom Department of Internal Medicine Hamad Medical CorporationDoha 0000Qatar Department of Neurology Faisalabad Medical UniversityFaisalabad 38000PunjabPakistan Department of Neurocritical Care AdventhealthOrlandoFlorida 33662United States

BACKGROUND Despite its high prevalence,migraine remains underdiagnosed worldwide.A significant reason is the knowledge gap in physicians regarding diagnostic criteria,clinical features,and other clinical aspects of migraine.AIM To measure the knowledge deficit in physicians and medical students and to assess the prevalence of migraine in the same population.METHODS An online questionnaire was developed and distributed among physicians and final year medical students on duty in various medical and surgical specialties of Allied and DHQ Hospitals,Faisalabad,between October 2018 and October 2019.Inclusion criteria were public practicing physicians who experience headaches,while those who never experienced headaches were excluded.Different questions assessed respondents on their knowledge of triggers,diagnosis,management,and prophylaxis of the migraine headache.They were asked to diagnose themselves using embedded ICHD-3 diagnostic criteria for different types of migraine.Graphs,tables,and figures were made using Microsoft Office 2016 and Microsoft Visio,and data analysis was done in R Studio 1.4.RESULTS We had 213 respondents and 175 fulfilled inclusion criteria,with 99(52%),58(30%)and 12(6.3%)belonging to specialties of medicine,surgery,and others,respectively.Both genders were symmetrically represented(88 male and 87 female).Fifty-two(24.4%)of our 213 respondents were diagnosed with migraine,with 26(50%)being aware of it.Females had higher prevalence among study participants(n=28,32.2%)compared to males(n=20,22.7%,P=0.19).A majority(62%)of subjects never consulted any doctor for their headache.Similarly,a majority(62%)either never heard or did not remember the diagnostic criteria of migraine.Around 38%falsely believed that having any type of aura is essential for diagnosing migraine.The consultation rate was 37%(n=65),and migraineurs were significantly more likely to have consulted a doctor,and a neurologist in particular(P<0.001).Consulters and migraineurs fared better in the knowledge of diagnostic aspects of th

关键词： Migraine Headache disorders Knowledge study Prevalence Knowledge Epidemiology Public health

Fusion-Based Machine Learning Architecture for Heart Disease Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第5期67卷 2481-2496页

作者： muhammad Waqas Nadeem Hock Guan Goh muhammad Adnan khan muzammil Hussain muhammad Faheem Mushtaq Vasaki a/p Ponnusamy Faculty of Information and Communication Technology(FICT) Universiti Tunku Abdul Rahman(UTAR)KamparPerak31900Malaysia Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The contemporary evolution in healthcare technologies plays a considerable and signicant role to improve medical services and save human lives.Heart disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes,as numerous people have been suffering from this disease globally.Heart attacks occur when the ranges of vital signs such as blood pressure,pulse rate,and body temperature exceed their normal values.The efcient diagnosis of heart diseases could play a substantial role in the eld of cardiology,while diagnostic time could be reduced.It has been a key challenge for researchers and medical experts to diagnose heart diseases accurately and timely.Therefore,machine learning-based techniques are used for the diagnosis with higher accuracy,using datasets compiled from former medical patients’reports.In recent years,numerous studies have been presented in the literature propose machine learning techniques for diagnosing heart diseases.However,the existing techniques have some limitations in terms of their accuracy.In this paper,a novel Support Vector Machine(SVM)based architecture for heart disease prediction,empowered with a fuzzy based decision level fusion,is presented.The SVMbased architecture has improved the accuracy signicantly as compared to existing solutions,where 96.23%accuracy has been achieved.

关键词： Heart disease machine learning support vector machine fuzzy logic fusion cardiovascular