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Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

Computers, Materials & Continua 2021年第9期68卷 3773-3787页

作者： Sajid Habib Gill Noor Ahmed Sheikh Samina Rajpar Zain ul Abidin N.Z.Jhanjhi Muneer Ahmad Mirza Abdur Razzaq Sultan S.Alshamrani Yasir malik Fehmi Jaafar Department of Computer Science Shah Abdul Latif UniversityKhairpur66020SindhPakistan National College of Business Administration&Economics Lahore54000Pakistan School of Computer Science and Engineering SCETaylor’s UniversityMalaysia Department of Information Systems Faculty of Computer Science&Information TechnologyUniversiti MalayaMalaysia Department of Information Technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Engineering&Computing SciencesNew York Institute of TechnologyVancouverCanada The Computer Research Institute of Montreal QuebecCanada

Medical data tampering has become one of the main challenges in the field of secure-aware medical data *** of normal patients’medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways ***,the integrity of these data can be *** detection is a method of detecting an anomaly in manipulated forged *** appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original *** neural networks(CNNs)have contributed a major breakthrough in this type of *** has been much interest from both the clinicians and the AI community in the possibility of widespread usage of artificial neural networks for quick diagnosis using medical data for early COVID-19 patient *** purpose of this paper is to detect forgery in COVID-19 medical data by using CNN in the error level analysis(ELA)by verifying the noise pattern in the *** proposed improved ELA method is evaluated using a type of data splicing forgery and sigmoid and ReLU phenomenon *** proposed method is verified by manipulating COVID-19 data using different types of forgeries and then applying the proposed CNN model to the data to detect the data *** results show that the accuracy of the proposed CNN model on the test COVID-19 data is approximately 92%.

关键词： Data security data privacy medical-data forgery COVID-19 convolutional neural network machine learning deep learning

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Deciphering key genes involved in cisplatin resistance in kidney renal clear cell carcinoma through a combined in silico and in vitro approach

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肿瘤学研究(英文) 2023年第6期31卷 899-916页

作者： MUNEEBA malik MAMOONA MAQBOOL TOOBA NISAR TAZEEM AKHTER JAVED AHMED UJAN ALANOOD SALGARNI FAKHRIA AAL JOUFI SULTAN SHAFI KALANAZI MOHAMMAD HADI ALMOTARED MOUNIR MSALEM BEKHIT MUHAMMAD JAMIL Services Hospital LahorePakistan Sabzazar Medical Center LahorePakistan BHU Pourmiana AttockPakistan Public Health Department University of Health SciencesLahorePakistan Department of Zoology Shah Abdul Latif UniversityKhairpurPakistan Department of Animal Sciences University of FloridaGainesvilleUSA Pharmacology and Toxicology Department College of Pharmacy Umm Al-Qura UniversityMakkahSaudi Arabia Department of Pharmacology College of PharmacyJouf UniversityAljoufSaudi Arabia Regional Laboratory and Blood Bank(Total Laboratory Automation) RiyadhSaudi Arabia Health Affairs in Najran New Najran General HospitalNajranSaudi Arabia Department of Pharmaceutics College of PharmacyKing Saud UniversityRiyadhSaudi Arabia PARC Arid Zone Research Center Dera Ismail KhanPakistan

The low survival rate of Kidney renal clear cell carcinoma(KIRC)patients is largely attributed to cisplatin *** than focusing solely on individual proteins,exploring protein-protein interactions could offer greater insight into drug *** this end,a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC *** genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information(NCBI)database using search terms as“Kidney renal clear cell carcinoma”and“Cisplatin resistance”.The genes retrieved were analyzed for hub gene identification using the STRING database and Cytoscape *** and promoter methylation profiling of the hub genes was done using UALCAN,GEPIA,OncoDB,and HPA ***,survival,functional enrichment,immune cell infiltration,and drug prediction analyses of the hub genes were performed using the cBioPortal,GEPIA,GSEA,TIMER,and DrugBank ***,expression and methylation levels of the hub genes were validated on two cisplatin-resistant RCC cell lines(786-O and A-498)and a normal renal tubular epithelial cell line(HK-2)using two high throughput techniques,including targeted bisulfite sequencing(bisulfite-seq)and RT-qPCR.A total of 124 genes were identified as being associated with cisplatin resistance in *** of these genes,MCL1,IGF1R,CCND1,and PTEN were identified as hub genes and were found to have significant(p<0.05)variations in their mRNA and protein expressions and effects on the overall survival(OS)of the KIRC ***,an aberrant promoter methylation pattern was found to be associated with the dysregulation of the hub *** addition to this,hub genes were also linked with different cisplatin resistance-causing ***,hub genes can be targeted with Alvocidib,Estradiol,Tretinoin,Capsaicin,Dronabinol,Metribolone,Calcitriol

关键词： KIRC Cisplatin resistance Chemotherapy Overall survival

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Thyroglossal Duct Anomalies in Pediatric and Adult Population: A 10-Year Experience in a Tertiary Care Hospital

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Surgical Science（外科学） 2021年第7期

作者： Montasir Junaid Ghaleb Al-Sayed Sayed Agha Ali shah Hareem U.Khan Ali Mahdi Al Qannass Nadeem W.malik Yahya Al Kahtani Ahmed Arghabi abdul Aziz Ali Binhossan Sadaf Qadeer Ahmed

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