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Breast Cancer Prediction with Gaussian Process Using Anthropometric Parameters
Sheikh Tonmoy;Habiba Khan Hiya;Md. Zahid Hasan;K. M. Zubair Hasan;Nusrat Zahan
2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2021 | Conference Paper |
In recent years, the breast cancer classification has piqued attention in the area of health-care informatics which is the second leading cause of mortality in women due to cancer. The spread of Breast Cancer growth and its high casualty has prodded a ton of research for contemplating its causes and medicines. The enormous number of genes and their entwining relations requires progressed AI models...Show More
A Multi-attribute Decision Making Approach for Trauma Center Site Selection
Kaniz Fatema;Md. Awlad Hossen Rony;Nusrat Zahan;Md. Zahid Hasan
2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2021 | Conference Paper |
To make sophisticated decisions considering multiple conflicting criteria, such as choosing the location of a new facility is common for environmental managers. The environment and health of city inhabitants are greatly damaged if the selection of a site is wrong. In a metropolitan city, site selection for a trauma center is a quite tough decision taken by policymakers. Considering the minimal tim...Show More
A Deep Learning-Based Approach for Edible, Inedible and Poisonous Mushroom Classification
Nusrat Zahan;Md Zahid Hasan;Md Abdul Malek;Sanjida Sultana Reya
2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)
Year: 2021 | Conference Paper |
Cited by: Papers (39)
Mushroom is one of the fungi types' food that has the most powerful nutrients on the plant. Nevertheless, the identification of edible, inedible and poisonous mushrooms among its existing species is a must due to its high demand for peoples' everyday meal and major advantage on medical science. For this purpose, deep learning approaches like InceptionV3, VGG16 and Resnet50 has been applied to iden...Show More
Multi-attribute Decision Making Approach for Waste Bin Site Selection Problem: A case study in Dhaka City
2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Site selection for the waste bin in a metropolitan city is one of the essential and critical decision problems taken by policymakers. An inappropriate site selection imposes excessive effects on the environment and health issues of city inhabitants. Nowadays, a multi-attribute decision-making approach is recommended to apply to progress exactness of decision making and lessen additional adverse. T...Show More
Integrated Use of Rough Sets and Artificial Neural Network for Skin Cancer Disease Classification
2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
The aim of this study is to build a classifier for predicting a disease existence by learning a least conventional set of features extracted from the clinical dataset. Rough set, indiscernibility relation method along with a feedforward neural network is applied and divided the whole process into two parts. At first part, the rough set method is considered as a reduction of features and selected a...Show More
Automated Prediction of Phishing Websites Using Deep Convolutional Neural Network
2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Phishing is one of the ruinous issues encountered by the World Wide Web (WWW) and steers to the financial catastrophes for individuals and businesses. It has been perpetually a perplexing issue to identify phishing attacks with high exactness. The tremendous outcomes in the area of classification have been succeeded by the state-of-the-art invention of the deep convolutional neural networks (DCNNs...Show More
Automated Prediction of Heart Disease Patients using Sparse Discriminant Analysis
K. M. Zubair Hasan;Shourob Datta;Md Zahid Hasan;Nusrat Zahan
2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)
Year: 2019 | Conference Paper |
Cited by: Papers (11)
Linear Discriminant Analysis (LDA) is an easy and efficient method for pattern classification, while it is also broadly utilized for the initial discovery of diseases using Electronic Health Records (EHR) data. Nonetheless, the performance of LDA for EHR data classification is recurrently influenced by two major factors: poor evaluation of LDA parameters (e.g., covariance matrix), and “linear inse...Show More
Simulation study on nonlinear ultrasound imaging using different realistic synthetic phantoms
2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Ultrasound imaging plays an important role in medical diagnosis which depends on two basic strategies either linear or nonlinear propagation of sound wave through tissues. Though linear ultrasound imaging has wide applications considering low cost, safe and portable facilities, it suffers poor SNR and resolutions. Harmonic imaging based on nonlinear response of tissue has significance as it is mor...Show More
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