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Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI

Computers, Materials & Continua 2023年第8期76卷 2551-2570页

作者： umair muneer butt Rimsha Arif Sukumar Letchmunan Babur Hayat Malik Muhammad Adil butt School of Computer Sciences Universiti Sains MalaysiaPenang1180Malaysia Department of Computer Science and IT The University of ChenabGujrat50700Pakistan

The detection of brain disease is an essential issue in medical and research *** learning techniques have shown promising results in detecting and diagnosing brain diseases using magnetic resonance imaging(MRI)*** techniques involve training neural networks on large datasets of MRI images,allowing the networks to learn patterns and features indicative of different brain ***,several challenges and limitations still need to be addressed further to improve the accuracy and effectiveness of these *** paper implements a Feature Enhanced Stacked Auto Encoder(FESAE)model to detect brain *** standard stack auto encoder’s results are trivial and not robust enough to boost the system’s ***,the standard Stack Auto Encoder(SAE)is replaced with a Stacked Feature Enhanced Auto Encoder with a feature enhancement function to efficiently and effectively get non-trivial features with less activation energy froman *** proposed model consists of four ***,pre-processing is performed to remove noise,and the greyscale image is converted to Red,Green,and Blue(RGB)to enhance feature details for discriminative feature ***,feature Extraction is performed to extract significant features for classification using DiscreteWavelet Transform(DWT)and ***,classification is performed to classify MRI images into four major classes:Normal,Tumor,Brain Stroke,and Alzheimer’***,the FESAE model outperforms the state-of-theart,machine learning,and deep learning methods such as Artificial Neural Network(ANN),SAE,Random Forest(RF),and Logistic Regression(LR)by achieving a high accuracy of 98.61% on a dataset of 2000 MRI *** proposed model has significant potential for assisting radiologists in diagnosing brain diseases more accurately and improving patient outcomes.

关键词： Brain diseases deep learning feature enhanced stacked auto encoder stack auto encoder

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Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

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Computers, Materials & Continua 2023年第3期74卷 5017-5033页

作者： umair muneer butt Hadiqa Aman Ullah Sukumar Letchmunan Iqra Tariq Fadratul Hafinaz Hassan Tieng Wei Koh School of Computer Sciences Universiti Sains MalaysiaPenang1180Malaysia Department of Computer Science The University of ChenabGujrat50700Pakistan Department of Software Engineering and Information System Universiti Putra MalaysiaSelangor43400Malaysia

Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social ***,dynamic environments and anthropometric differences between individuals make it harder to recognize *** study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world *** uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural ***,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification *** state-of-the-art pre-trained models are exploited to find the best model for spatial feature *** temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture *** state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation *** addition,seven state-of-the-art optimizers are used to fine-tune the proposed network ***,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB *** contrast,the other uses optical flow ***,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets.

关键词： Human activity recognition deep learning transfer learning neural network ensemble learning spatio-temporal

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Insight into the phytochemical, biological, and in silico studies of Erythrina suberosa roxb.: A source of novel therapeutic bioactive products from a medicinal plant

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Food Bioscience 2023年第2期52卷 1421-1432页

作者： Abdulhakeem S.Alamri Hammad Saleem Irfan Pervaiz umair Khurshid Juwairiya butt Tahir Ali Chohan Majid Alhomrani Marcello Locatelli Syafiq Asnawi Zainal Abidin Yasir Nasser H Alqahtani Kannan RRRengasamy Mohamad Fawzi Mahomoodally Department of Clinical Laboratory Sciences The Faculty of Applied Medical SciencesTaif UniversityTaifSaudi Arabia Centre of Biomedical Sciences Research(CBSR) Deanship of Scientific ResearchTaif UniversitySaudi Arabia Institute of Pharmaceutical Sciences(IPS) University of Veterinary&Animal Sciences(UVAS)LahorePakistan KITAAS Khaldunia College of PharmacyLahorePakistan Department of Pharmaceutical Chemistry Faculty of PharmacyThe Islamia University of Bahawalpur63100Pakistan School of Life Sciences University of Westminster115 New Cavendish StreetLondonW1W 6UWUK Department of Pharmacy University‘G.d’Annunzio of Chieti-Pescara66100ChietiItaly Jeffrey Cheah School of Medicine and Health Sciences Monash University MalaysiaJalan Lagoon Selatan47500Bandar SunwaySelangor Darul EhsanMalaysia MOI Clinics Security Forces HospitalRiyadhSaudi Arabia Laboratory of Natural Products and Medicinal Chemistry(LNPMC) Department of PharmacologySaveetha Dental CollegeSaveetha Institute of Medical and Technical Sciences(SIMATS)Chennai600077India Department of Health Sciences Faculty of Medicine and Health SciencesUniversity of MauritiusR´eduit80837Mauritius Centre of Excellence for Pharmaceutical Sciences North-West UniversityPrivate Bag X6001Potchefstroom2520South Africa

Background:Erythrina suberosa(***)*** known as corky coral tree is used as a folklore medicine to treat ulcers and *** study explored the phytochemical profiles of methanol and dichloromethane(DCM)extracts from the aerial,root,and flower parts of ***:Total bioactive contents,high-performance liquid chromatography array(HPLC-PDA)polyphenolic quantification,and ultra-high performance liquid chromatography-mass spectrometry(UHPLC-MS)analysis were used to evaluate the phytochemical *** potential was evaluated by determining their antioxidant(DPPH,ABTS,FRAP,CUPRAC,Phosphomolybdenum,and metal chelating)and enzyme inhibitory(cholinesterase,amylase,glucosidase,and tyrosinase)***:The phenolic(46.26 mg GAE/g extract)and flavonoid(32.46 mg QE/g extract)contents were found to be highest in the methanolic extract of roots(EsR-M).HPLC-PDA analysis determined the presence of numerous bioactive compounds,including catechin,syringic acid,p-hydroxy benzoic acid,gallic acid,vanillic acid,epicatechin,rutin,chlorogenic acid,carvacrol,sinapinic acid,and naringenin in considerable amounts.A total of 143 phytochemicals,belonging to phenolic,flavonoid,coumarin,terpenoid,chalcone,saponin,and glycoside classes,were tentatively identified by UHPLC-MS *** methanolic extract(EsA-M)exhibited highest radical scavenging(DPPH 86.81 mgTE/g extract,ABTS 245.17 mgTE/g extract)as well as reducing potential(FRAP 177.12 mgTE/g extract,CUPRAC 177.12 mgTE/g extract).Likewise,it was also noted to be most active for BChE(5.70 mg GALAE/g extract)and tyrosinase inhibition(148.35 mg KAE/g extract).While,roots-DCM extract(EsR-D)presented considerable inhibition for AChE(4.69 mg GALAE/g extract)and amylase(0.81 mmol ACAE/g extract)***,davallioside A,and isovitexin were docked to tyrosinase to depict possible ***:This study has established baseline data on the biological and phytochemical profile of ***

关键词： Erythrina suberosa HPLC-PDA UHPLC-MS Antioxidant Enzyme inhibition Natural products

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Digestive system involvement and clinical outcomes among COVID-19 patients:A retrospective cohort study from Qatar

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World Journal of Gastroenterology 2021年第46期27卷 7995-8009页

作者： Muhammad umair Khan Kamran Mushtaq Deema Hussam Alsoub Phool Iqbal Fateen Ata Hammad Shabir Chaudhry Fatima Iqbal Girisha Balaraju Muna A Al Maslamani Betsy Varughese Rajvir Singh Khalid Al Ejji Saad Al Kaabi Yasser Medhat Kamel Adeel Ajwad butt Department of Gastroenterology and Hepatology Hamad Medical CorporationDoha 3050Qatar ECPEExecutive and Continuing Professional Education Harvard T.H Chan School of Public HealthBostonMA 02115-5810United States Department of Palliative Care National Center for Cancer Care&ResearchHamad Medical CorporationDoha 3050Qatar Department of Medicine Hamad Medical CorporationDoha 3050Qatar Department of Infectious Disease Communicable Disease CenterHamad Medical CorporationDoha 3050Qatar Department of Cardiology Research Heart HospitalHamad Medical CorporationDoha 3050Qatar Department of Medicine Division of Infectious DiseasesWeill Cornell Medical CollegeNew YorkNY 10075United States Department of Medicine Weill Cornell Medical College-QatarDoha 24144Qatar

BACKGROUND Coronavirus disease 2019(COVID-19)caused by the severe acute respiratory syndrome coronavirus 2 virus most commonly presents with respiratory *** gastrointestinal(GI)manifestations either at presentation or during hospitalization are also common,their impact on clinical outcomes is *** studies have described worse outcomes in COVID-19 patients with GI symptoms,while others have shown either no association or a protective *** is a need for consistent standards to describe GI symptoms in COVID-19 patients and to assess their effect on clinical outcomes,including mortality and disease *** To investigate the prevalence of GI symptoms in hospitalized COVID-19 patients and their correlation with disease severity and clinical *** We retrospectively reviewed 601 consecutive adult COVID-19 patients requiring hospitalization between May 1-15,*** symptoms were recorded at admission and during ***,clinical,laboratory,and treatment data were *** outcomes included all-cause mortality,disease severity at presentation,need for intensive care unit(ICU)admission,development of acute respiratory distress syndrome,and need for mechanical *** logistic regression model was used to identify independent predictors of the adverse *** The prevalence of any GI symptom at admission was 27.1%and during hospitalization was 19.8%.The most common symptoms were nausea(98 patients),diarrhea(76 patients),vomiting(73 patients),and epigastric pain or discomfort(69 patients).There was no difference in the mortality between the two groups(6.21%vs 5.5%,P=0.7).Patients with GI symptoms were more likely to have severe disease at presentation(33.13%vs 22.5%,P<0.001)and prolonged hospital stay(15 d vs 14 d,P=0.04).There was no difference in other clinical outcomes,including ICU admission,development of acute respiratory distress syndrome,or need for mechanical ventil

关键词： COVID-19 Gastrointestinal manifestations Mortality Intensive care unit admission Mechanical ventilation Disease severity

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急性消化道出血应首先提高内窥镜的利用率

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英国医学杂志中文版 2009年第1期12卷 63-63页

作者： Mohammed A butt umair A Mohammed Anne B Ballinger Queen Elizabeth the Queen Mother Hospital Margate East Kent C39 4AN specialty registrar gastroenterology Queen Elizabeth the Queen Mother Hospital Margate East Kent C39 4ANmedical student Queen Elizabeth the Queen Mother Hospital Margate East Kent C39 4AN consultant gastroenterologist

Palmer和Naim总结的SIGN指南（见本期第57页）推荐：在医疗条件可能的医院，应让患者于入院24小时内尽早接受内窥镜检查和治疗，而不应在内镜治疗前仅使用质子泵抑制剂。

关键词：内窥镜检查急性消化道出血利用率质子泵抑制剂医疗条件治疗前

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