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| 1 | Graphene-Coated Optical Fiber SPR Biosensor for BRCA1 and BRCA2 Breast Cancer Biomarker Detection:a Numerical Design-Based Analysis显示文摘This paper provides a simple hybrid design and numerical analysis of the graphene-coated fiber-optic surface plasmon resonance(SPR)biosensor for breast cancer gene-1 early onset(BRCA1)and breast cancer gene-2 early onset(BRCA2)genetic breast cancer detection.Two specific mutations named 916delTT and 6174delT in the BRCA1 and BRCA2 are selected for numerical detection of breast cancer.This sensor is based on the technique of the attenuated total reflection(ATR)method to detect deoxyribonucleic acid(DNA)hybridization along with individual point mutations in BRCA1 and BRCA2 genes.We have numerically shown that momentous changes present in the SPR angle(minimum:135%more)and surface resonance frequency(SRF)(minimum:136%more)for probe DNA with various concentrations of target DNA corresponding to a mutation of the BRCA1 and BRCA2 genes.The variation of the SPR angle and SRF for mismatched DNA strands is quite negligible,whereas that for complementary DNA strands is considerable,which is essential for proper detection of genetic biomarkers(916delTT and 6174delT)for early breast cancer.At last,the effect of electric field distribution in inserting graphene layer is analyzed incorporating the finite difference time domain(FDTD)technique by using Lumerical FDTD solution commercial software.To the best of our knowledge,this is the first demonstration of such a highly efficient biosensor for detecting BRCA1 and BRCA2 breast cancer.Therefore,the proposed biosensor opens a new window toward the detection of breast cancers. | Md.Biplob HOSSAIN Md.Muztahidul ISLAM Lway Faisal ABDULRAZAK Md.Masud RANA Tarik Bin Abdul AKIB Mehedi HASSAN | 2020 | Photonic Sensors2020，10，1： | 4 |
| 2 | Guest Editorial for Special Issue on Blockchain for Internet-of-Things and Cyber-Physical Systems显示文摘Cyber-physical systems(CPS)are increasingly commonplace,with applications in energy,health,transportation,and many other sectors.One of the major requirements in CPS is that the interaction between cyber-world and man-made physical world(exchanging and sharing of data and information with other physical objects and systems)must be safe,especially in bi-directional communications.In particular,there is a need to suitably address security and/or privacy concerns in this human-in-the-loop CPS ecosystem.However,existing centralized architecture models in CPS,and also the more general IoT systems,have a number of associated limitations,in terms of single point of failure,data privacy,security,robustness,etc.Such limitations reinforce the importance of designing reliable,secure and privacy-preserving distributed solutions and other novel approaches,such as those based on blockchain technology due to its features(e.g.,decentralization,transparency and immutability of data).This is the focus of this special issue. | Mohammad Mehedi Hassan Giancarlo Fortino Laurence T.Yang Hai Jiang Kim-Kwang Raymond Choo Jun Jason Zhang Fei-Yue Wang | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，12： | 2 |
| 3 | A market-oriented dynamic collaborative cloud services platform显示文摘 | Hassan Mohammad Mehedi Song B | 2010 | Annals of Telecommunications-Annales Des Telecommunications2010，，： | 1 |
| 4 | Transparent and Accurate COVID-19 Diagnosis:Integrating Explainable AI with Advanced Deep Learning in CT Imaging显示文摘In the current landscape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,especially in chest computed tomography(CT)scan analysis for virus detection,has become increasingly significant.Despite its potential,deep learning’s“black box”nature has been a major impediment to its broader acceptance in clinical environments,where transparency in decision-making is imperative.To bridge this gap,our research integrates Explainable AI(XAI)techniques,specifically the Local Interpretable Model-Agnostic Explanations(LIME)method,with advanced deep learning models.This integration forms a sophisticated and transparent framework for COVID-19 identification,enhancing the capability of standard Convolutional Neural Network(CNN)models through transfer learning and data augmentation.Our approach leverages the refined DenseNet201 architecture for superior feature extraction and employs data augmentation strategies to foster robust model generalization.The pivotal element of our methodology is the use of LIME,which demystifies the AI decision-making process,providing clinicians with clear,interpretable insights into the AI’s reasoning.This unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates the precision in detecting COVID-19 cases but also equips healthcare professionals with a deeper understanding of the diagnostic process.Our method,validated on the SARS-COV-2 CT-Scan dataset,demonstrates exceptional diagnostic accuracy,with performance metrics that reinforce its potential for seamless integration into modern healthcare systems.This innovative approach marks a significant advancement in creating explainable and trustworthy AI tools for medical decisionmaking in the ongoing battle against COVID-19. | Mohammad Mehedi Hassan Salman A.AlQahtani Mabrook S.AlRakhami Ahmed Zohier Elhendi | 2024 | Computer Modeling in Engineering & Sciences2024，139，6： | 0 |
| 5 | Role of H2 receptor blocker famotidine over the clinical recovery of COVID-19 patients: A randomized controlled trial显示文摘BACKGROUND Coronavirus disease 2019(COVID-19)is a global pandemic putting the population at a high risk of infection-related health hazards,mortality and a potential failure of proper medical therapies.Therefore,it is necessary to evaluate the potential use of the existing drugs that could be used as options for the medical management of COVID-19 patients.AIM To evaluate the role of the H_(2) receptor blocker“famotidine”in COVID-19 illness.METHODS This study was done on seriously ill COVID-19 patients admitted to the intensive care unit(ICU)from different institutes in Bangladesh.Patients were divided into famotidine treatment group“A”(famotidine 40 mg to 60 mg oral formulation every 8 h with other treatment as given),and control group“B”(treatment as given).National early warning score(NEWS)-2,and sequential organ failure assessment day-1 score was calculated to evaluate the outcome.Outcomes were evaluated by the time required for clinical improvement,characterized as duration required from enrollment to the achievement of NEWS-2 of≤2 maintained for 24 h;time to symptomatic recovery,defined as the duration in days(from randomization)required for the recovery of the COVID-19 symptoms;mortality rate;duration of ICU and hospital stay;total period of hospitalization;the rate of supplementary oxygen requirement;the computed tomography(CT)chest recovery(%),the time required for the viral clearance and“NEWS-2”on discharge.RESULTS A total of 208 patients were enrolled in this study with 104 patients in each group.The famotidine treatment group had comparatively better recovery of 75%and a low mortality of 25%than the control with a recovery of 70%and a mortality of 30%.Duration of clinical improvement(group A 9.53 d,group B 14.21 d);hospitalization period among the recovered patients(group A 13.04 d,group B 16.31 d),pulmonary improvement in chest CT(group A 21.7%,group B 13.2%),and the time for viral clearance(group A 20.7 d,group B 23.8 d)were found to be statistically significant P≤0.05.However,the Kaplan Meier survival test was not significant among the two study groups,P=0.989.CONCLUSION According to our study,treatment with famotidine achieved a better clinical outcome compared to the control group in severe COVID-19 illness,although no significant survival benefit was found. | Abu Taiub Mohammed Mohiuddin Chowdhury Aktar Kamal Md Kafil Uddin Abbas Md Rezaul Karim Md Ahsan Ali Shubhashis Talukder H M Hamidullah Mehedi Hamid Hassan Abul Hossain Shahin Yarui Li Shuixiang He | 2022 | World Journal of Clinical Cases2022，10，23： | 0 |
| 6 | NPEST: a nonparametric method and a database for transcription start site prediction显示文摘 | Tatiana Tatarinova Alona Kryshchenko Martin Triska Mehedi Hassan Denis Murphy Michael Neely Alan Schumitzky | 2013 | Frontiers of Electrical and Electronic Engineering in China2013，8，4： | 0 |
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