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Cardiac implications in myasthenia gravis

World Journal of Clinical Cases 2024年第26期12卷 5863-5867页

作者： praveen reddy elmati Gowthami Sai Kogilathota Jagirdhar Salim Surani Department of Anesthesiology Saint Clair HospitalDoverNJ 07801United States Department of Medicine Saint Michaels Medical CenterNewarkNJ 07107United States Department of Medicine and Pharmacology Texas A&M UniversityCollege StationTX 77843United States

This editorial aimed to consolidate the current evidence in literature on the association between myasthenia gravis(MG)and cardiac involvement,focusing on the impact of thymoma,antistriational antibodies,and late-onset ***,the study aimed to explore the influence of genetic differences among populations on the association with cardiac *** conducted a review of existing literature in PubMed and Google Scholar to find relevant studies on cardiac involvement in *** created search criteria using a combination of free text words,including MG,antistriational antibodies,thymectomy,cardiomyopathy,myocarditis,arrhythmias,autonomic *** articles published in English language were analyzed and *** findings indicate a strong association between thymoma,myasthenic crisis,antistriational antibodies,and late-onset MG with cardiac *** study also revealed that genetic differences among populations influence the risk of cardiac disease and electrocardiography(ECG)abnormalities in MG *** dysfunctions altered cardiac autonomic response and increased susceptibility to arrhythmias and sudden cardiac death in MG *** study supports the significance of thymoma,antistriational antibodies,and late-onset MG as key factors associated with cardiac involvement in MG *** emphasizes the importance of ECG as the initial test in managing MG patients,particularly in the perioperative period,to identify and genetic testing if needed to address their cardiac risk effectively.

关键词： Myasthenia gravis Antistriational antibodies Thymectomy Cardiomyopathy Myocarditis Arrhythmias Autonomic dysfunction

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Remimazolam in intensive care unit:Potential applications and considerations

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World Journal of Critical Care Medicine 2024年第3期13卷 25-31页

作者： praveen reddy elmati Teja Nagaradona Gowthami Sai Kogilathota Jagirdhar Salim Surani Department of Anesthesiology Saint Clair HospitalDoverNJ 07801United States School of Medicine St George UniversityGranada SW170BDWest Indies Department of Medicine Saint Michaels Medical CenterNewarkNJ 07107United States Department of Medicine&Pharmacology Texas A&M UniversityCollege StationTX 77843United States

This manuscript explores the potential use of Remimazolam in the intensive care unit(ICU)and critical care units,considering its pharmacological characteristics,clinical applications,advantages,and comparative effectiveness over current sedatives and *** reviewed existing PubMed and Google Scholar literature to find relevant studies on Remimazolam in *** created search criteria using a combination of free text words,including Remimazolam,critical care,intensive care,sedation,anesthesia,pharmacokinetics,and *** articles published in the English language were analyzed and *** is an ultra-short-acting benzodiazepine derivative promising for sedation and *** is a safer option for hemodynamically unstable,elderly,or liver or kidney *** also has comparable deep sedation properties to propofol in the ***,it reduces post-procedural delirium and patient comfort and reduces the need for additional sedatives in pediatric *** conclusion,Remimazolam is an excellent alternative to current sedatives and anesthetics in the *** cost is comparable to that of current *** research on its long-term safety in the ICU and its broader application and incorporation into routine use is necessary.

关键词： Remimazolam Intensive care Critical care Anesthesia Sedation Mechanical ventilation Benzodiazepine

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Association of non-alcoholic fatty liver and metabolic-associated fatty liver with COVID-19 outcomes:A systematic review and metaanalysis

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World Journal of Gastroenterology 2023年第21期29卷 3362-3378页

作者： Gowthami Sai Kogilathota Jagirdhar Rakhtan K Qasba Harsha Pattnaik Kaanthi Rama Akshat Banga Shiva Teja reddy Anna Carolina Flumignan Bucharles Rahul Kashyap praveen reddy elmati Vikas Bansal Yatinder Bains Theodore DaCosta Salim Surani Department of Medicine Saint Michaels Medical CenterNewarkNJ 07102United States Department of Medicine Green Life Medical College and HospitalDhaka 1205Bangladesh Department of Medicine Lady Hardinge Medical CollegeNew Delhi 110001India Department of Medicine Gandhi Medical CollegeTelangana 500003India Department of Medicine Sawai Man Singh Medical CollegeJaipur 302004RajistanIndia Department of Medicine Universidade PositivoCuritiba 81290-000PRBrazil Research WellSpan HealthYorkPA 17403United States Department of Interventional Pain Medicine University of LouisvilleLouisvilleKY 40292United States Department of Internal Medicine Mayo ClinicRochesterMN 55902United States Department of Gastroenterology Saint Michaels Medical CenterNewarkNJ 07102United States Department of Medicine Texas A&M UniversityCollege StationTX 77843United States

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)and metabolic-associated fatty liver disease(MAFLD)are on the rise like any other liver disease,and tend to affect 25%of the United States *** impact of NAFLD and MAFLD on patients with coronavirus disease 2019(COVID-19)remains *** To identify the association of NAFLD and MAFLD with mortality,hospitalization,hospital length of stay,and supplemental oxygen utilization in COVID-19 *** A systematic review of literature on Cochrane,Embase,PubMed,ScienceDirect,and Web of Science databases was conducted from January 2019 to July *** that evaluated NAFLD/MAFLD using laboratory methods,noninvasive imaging,or liver biopsy were *** study protocol was registered in PROSPERO(ID CRD42022313259)and PRISMA guidelines were *** National Institutes of Health quality assessment tool was used to assess the quality of the *** analysis was conducted using software Rev Man version *** stability of the results was assessed using sensitivity *** Thirty-two studies with 43388 patients were included in the meta-analysis of whom 8538(20%)patients were observed to have *** were 42254 patients from 28 studies included in the mortality analysis.A total of 2008 patients died from COVID-19;837(10.52%)in the NAFLD group and 1171(3.41%)in the non-NAFLD *** odds ratio(OR)was 1.38 for mortality with a 95%confidence interval(95%CI)=0.97-1.95 and P=0.07.A total of 5043 patients from eight studies were included in the hospital length of stay *** were 1318 patients in the NAFLD group and 3725 patients in the non-NAFLD group.A qualitative synthesis showed that the mean difference in hospital length of stay was about 2 d between the NAFLD and non-NAFLD groups with a 95%CI=0.71-3.27 and P=*** hospitalization rates,the OR was 3.25 with a 95%CI of 1.73-6.10 and P=*** supplemental oxygen utilization,the OR was 2.04 with a 95%CI of 1.17-3.5

关键词： Non-alcoholic fatty liver Fatty liver Coronavirus COVID-19 Metabolic-associated fatty liver

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A Study on Outlier Detection and Feature Engineering Strategies in Machine Learning for Heart Disease Prediction

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Computer Systems Science & Engineering 2024年第5期48卷 1085-1112页

作者： Varada Rajkumar Kukkala Surapaneni Phani praveen Naga Satya Koti Mani Kumar Tirumanadham Parvathaneni Naga Srinivasu Department of Computer Science&Engineering(AIML) MLR Institute of TechnologyHyderabad500043India Department of Computer Science and Engineering Prasad V.Potluri Siddhartha Institute of TechnologyVijayawada520007India Department of Computer Science&Engineering Sir C.R.Reddy College of EngineeringEluru534001India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravati522503India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil

This paper investigates the application ofmachine learning to develop a response model to cardiovascular problems and the use of AdaBoost which incorporates an application of Outlier Detection methodologies namely;Z-Score incorporated with GreyWolf Optimization(GWO)as well as Interquartile Range(IQR)coupled with Ant Colony Optimization(ACO).Using a performance index,it is shown that when compared with the Z-Score and GWO with AdaBoost,the IQR and ACO,with AdaBoost are not very accurate(89.0%vs.86.0%)and less discriminative(Area Under the Curve(AUC)score of 93.0%vs.91.0%).The Z-Score and GWO methods also outperformed the others in terms of precision,scoring 89.0%;and the recall was also found to be satisfactory,scoring 90.0%.Thus,the paper helps to reveal various specific benefits and drawbacks associated with different outlier detection and feature selection techniques,which can be important to consider in further improving various aspects of diagnostics in cardiovascular ***,these findings can enhance the knowledge of heart disease prediction and patient treatment using enhanced and innovativemachine learning(ML)*** findings when combined improve patient therapy knowledge and cardiac disease prediction through the use of cutting-edge and improved machine learning *** work lays the groundwork for more precise diagnosis models by highlighting the benefits of combining multiple optimization *** studies should focus on maximizing patient outcomes and model efficacy through research on these combinations.

关键词： Grey wolf optimization ant colony optimization Z-Score interquartile range(IQR) AdaBoost outlier

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Deep Neural Networks Based Approach for Battery Life Prediction

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Computers, Materials & Continua 2021年第11期69卷 2599-2615页

作者： Sweta Bhattacharya praveen Kumar reddy Maddikunta Iyapparaja Meenakshisundaram Thippa reddy Gadekallu Sparsh Sharma Mohammed Alkahtani Mustufa Haider Abidi School of Information Technology and Engineering Vellore Institute of TechnologyVelloreIndia Department of Computer Science and Engineering Baba Ghulam Shah Badshah UniversityRajouriIndia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadhSaudi Arabia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadhSaudi Arabia

The Internet of Things(IoT)and related applications have witnessed enormous growth since its *** diversity of connecting devices and relevant applications have enabled the use of IoT devices in every *** the applicability of these applications are predominant,battery life remains to be a major challenge for IoT devices,wherein unreliability and shortened life would make an IoT application completely *** this work,an optimized deep neural networks based model is used to predict the battery life of the IoT *** present study uses the Chicago Park Beach dataset collected from the publicly available data repository for the experimentation of the proposed *** dataset is pre-processed using the attribute mean technique eliminating the missing values and then One-Hot encoding technique is implemented to convert it to numerical *** processed data is normalized using the Standard Scaler *** Flame Optimization(MFO)Algorithm is then implemented for selecting the optimal features in the *** optimal features are finally fed into the DNN model and the results generated are evaluated against the stateof-the-art models,which justify the superiority of the proposed MFO-DNN model.

关键词： Battery life prediction moth flame optimization one-hot encoding standard scaler

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An Efficient Sound and Data Steganography Based Secure Authentication System

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Computers, Materials & Continua 2021年第4期67卷 723-751页

作者： Debajit Datta Lalit Garg Kathiravan Srinivasan Atsushi Inoue G.Thippa reddy M.praveen Kumar reddy K.Ramesh Nidal Nasser School of Computer Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India Faculty of Information and Communication Technology University of MaltaMsidaMSD2080Malta School of Information Technology and Engineering Vellore Institute of Technology(VIT)Vellore632014India Department of Information Systems&Business Analytics Eastern Washington UniversitySpokaneWA99202USA Department of Computer Science Karnataka State Akkamahadevi Women’s UniversityVijayapuraIndia College of Engineering Alfaisal UniversityRiyadh1153Saudi Arabia

The prodigious advancements in contemporary technologies have also brought in the situation of unprecedented ***,the pin-based security system is an inadequate mechanism for handling such a *** reason is that hackers use multiple strategies for evading security systems and thereby gaining access to private *** research proposes to deploy diverse approaches for authenticating and securing a connection amongst two devices/gadgets via sound,thereby disregarding the pins’manual ***,the results demonstrate that the proposed approaches outperform conventional pin-based authentication or QR authentication ***,a random signal is encrypted,and then it is transformed into a wave file,after which it gets transmitted in a short burst via the device’s ***,the other device/gadget captures these audio bursts through its microphone and decrypts the audio signal for getting the essential data for ***,this model requires two devices/gadgets with speakers and a microphone,and no extra hardware such as a camera,for reading the QR code is *** first module is tested with realtime data and generates high scores for the widely accepted accuracy metrics,including precision,Recall,F1 score,entropy,and mutual information(MI).Additionally,this work also proposes a module helps in a secured transmission of sensitive data by encrypting it over images and other *** steganographic module includes two-stage encryption with two different encryption algorithms to transmit data by embedding inside a *** encryption algorithms and their combinations are taken for this system to compare the resultant file *** these systems engender high accuracies and provide secure connectivity,leading to a sustainable communication ecosystem.

关键词： Cyber-attacks signals privacy security organization encryption decryption authentication effective communication steganography

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Holmes Heart and HIV: A Rare Combination of Two “H”s in a 23-Year-Old Widow

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International Journal of Clinical Medicine 2016年第7期7卷 450-453页

作者： Adikesava Naidu Otikunta praveen Kumar Alane YV Subba reddy Syed Imamuddin Department of Cardiology Osmania General Hospital and Osmania Medical College Hyderabad India

A 23-year-old, lean, scoliotic female presented to our hospital with a history of shortness of breath and cyanosis on exertion. Her 2D echocardiography revealed single left ventricle with both atrio-ventricular valves opening in it. She had normally related great arteries, with severe pulmonary artery hypertension, without pulmonary stenosis. Her blood tests indicated that she was reactive to human immunodeficiency virus (HIV-1). The patients died within 2 months despite treatments with anti-retroviral therapy and decongestive therapy.

关键词： Double-Inlet Left Ventricle HIV Holmes Heart Left Ventricular Hypertrophy Rudimentary Right Ventricle

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Energy-and trust-aware secure routing algorithm for big data classification using MapReduce framework in IoT networks

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International Journal of Modeling, Simulation, and Scientific Computing 2021年第2期12卷 80-103页

作者： S.Md.Mujeeb R.praveen Sam K.Madhavi Department of CSE Jawaharlal Nehru Technological University Anantapur(JNTUA)Ananthapuramu-515002 Andhra PradeshIndia Department of Computer Science and Engineering G.Pulla reddy Engineering College(Autonomous)Nandyal Road Kurnool 518007Andhra PradeshIndia

Due to the open nature of wireless data transmission,routing and data security pose an important research challenge in the Internet of Things(IoT)-enabled ***,the characteristic features,like constrained resources,heterogeneity,uncontrolled environment,and scalability requirement,make the security issues even more ***,an effective and secure routing protocol named modified Energy Harvesting Trust-aware Routing Algorithm(mod-EHTARA)is proposed to increase the energy efficiency and the lifespan of the *** proposed mod-EHTARA is designed by adopting the Link Lifetime(LLT)model with the traditional *** optimal secure routing path is effectively selected by the proposed mod-EHTARA using the cost metric,which considers the factors like delay,LLT,energy,and *** big data classification process is carried out at the Base Station(BS)using the MapReduce ***,the big data classification is progressed using a stacked autoencoder,which is trained by the Adaptive E-Bat *** Adaptive E-Bat algorithm is developed by integrating the adaptive concept with the Bat Algorithm(BA)and Exponential Weighted Moving Average(EWMA).The proposed mod-EHTARA showed better performance by obtaining a maximal energy of 0.9855.

关键词： Stacked autoencoder big data classification Internet of Things secure routing energy harvesting

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