Browsing by Author "Alam, Saidul"

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    Early Prediction of Chronic Kidney Disease
    (Daffodil International University, 22-08-29) Mondol, Chaity; Shamrat, F. M. Javed Mehedi; Hasan, Md. Robiul; Alam, Saidul; Ghosh, Pronab; Tasnim, Zarrin; Ahmed, Kawsar; Bui, Francis M.; Ibrahim, Sobhy M.
    Chronic kidney disease (CKD) is one of the most life-threatening disorders. To improve survivability, early discovery and good management are encouraged. In this paper, CKD was diagnosed using multiple optimized neural networks against traditional neural networks on the UCI machine learning dataset, to identify the most efficient model for the task. The study works on the binary classification of CKD from 24 attributes. For classification, optimized CNN (OCNN), ANN (OANN), and LSTM (OLSTM) models were used as well as traditional CNN, ANN, and LSTM models. With various performance matrixes, error measures, loss values, AUC values, and compilation time, the implemented models are compared to identify the most competent model for the classification of CKD. It is observed that, overall, the optimized models have better performance compared to the traditional models. The highest validation accuracy among the tradition models were achieved from CNN with 92.71%, whereas OCNN, OANN, and OLSTM have higher accuracies of 98.75%, 96.25%, and 98.5%, respectively. Additionally, OCNN has the highest AUC score of 0.99 and the lowest compilation time for classification with 0.00447 s, making it the most efficient model for the diagnosis of CKD.
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    RentUs Bd
    (Daffodil International University, 23-02-18) Hasan, Md. Robiul; Alam, Saidul
    "RentUsBd" connects renters and property owners online. Where renters can easily find their property. Today's urban renters need help finding suitable housing. Given the circumstances, a collaborative online space might be of great assistance. These apps allow property owners and renters to sign up, and renters can use them to find available properties by communicating with owners. This project created an online rental management app for property owners and renters. This web application is useful and easy to use, and it has many features that renters won't find on any other Bangladeshi house-rental website. The app made it easier and faster to find properties and ensured more rental options. once This web app will improve nationwide service. Its smart features inspired an online bright property rental service.