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HPML-CVD: Hyperparameter Tuned Machine Learning Model to Predict Cardiovascular Disease

Biomedical Materials and Devices 2025年 1-15页

作者： Uddin, Nazim Hossain, Md. Sahadat Mahmud, Md. Zulfiker Ferdous, Rebina Talukder, Md. Alamin Department of Information and Communication Technology Chandpur Science and Technology University Chandpur Bangladesh Department of Computer Science and Engineering Jagannath University Dhaka Bangladesh Basic and Applied Research on Jute Project Bangladesh Jute Research Institute Dhaka 1207 Bangladesh Department of Computer Science and Engineering International University of Business Agriculture and Technology Dhaka Bangladesh

Cardiovascular disease (CVD) remains a significant global health concern, necessitating early detection and accurate prediction for effective intervention. Machine learning (ML) offers a data-driven approach to analyzing patient data, identifying complex patterns, and predicting CVD risk factors such as blood pressure, cholesterol, and genetic predispositions. This study employs the Heart Disease UCI dataset, comprising 303 cases and 14 attributes, to develop predictive ML models. A comprehensive feature engineering approach was applied, including Chi-Square feature selection, where the 10 most influential features were identified to enhance model performance. After feature selection, hyperparameter tuning was performed to optimize five classifiers: Random Forest, K-Nearest Neighbors, Decision Tree, Support Vector Machine, and Logistic Regression. The results indicate significant improvements in accuracy after feature engineering and fine-tuning, with the Random Forest classifier achieving the highest accuracy of 93.41%, outperforming previous work on the same dataset by 3.41%, followed by SVM at 91.21%. These findings underscore the potential of ML in early CVD prediction, emphasizing its role in proactive risk management and healthcare. The integration of ML-driven CVD risk assessment paves the way for personalized healthcare, benefiting both patients and medical professionals by facilitating early intervention, improving patient outcomes, and optimizing healthcare resource allocation. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Cardiovascular disease Cleveland dataset Heart disease prediction Logistic regression Machine learning

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Nutritional composition of some jute genotypes as vegetables

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International Journal of Vegetable Science 2020年第5期26卷 506-515页

作者： Tareq, Zablul Bashar, Kazi Khayrul Amin, Ruhul Sarker, Muhammad Delwar Hossain Moniruzzaman, Md. Sarker, Mohammad Saiful Alam Islam, Shahidul Basic and Applied Research on Jute Project Bangladesh Jute Research Institute Dhaka Bangladesh

jute (Corchorus sp.) is consumed as a leafy vegetable in many parts of the world. There is little information on nutritional composition of cultivated jute species and their wild relatives. To determine nutritional components of jute leaf, 3 C. capsularis L., germplasm, ‘Merha red’, ‘Merha green’, ‘Birol red’, a C. olitorius L., ‘Accession-3840ʹ, and ‘BJRI deshi pat shak-1ʹ and ‘BINA pat shak-1ʹ were examined, with the latter 2 as controls. In most cases, the four wild species contained more vitamins and minerals, and had more surviving plants per unit area, compared with controls. The highest percent protein and ash, highest leaf area, and most leaves per plant, were in the controls. The desired biochemical properties with high heritability and genetic advance can likely be transmitted from wild germplasm to cultivated C. capsularis species through crossing, but evaluation in other agro-climatic regions is needed to determine the efficacy of wild germplasm as donor parent. © 2019 Taylor & Francis Group, LLC.

关键词： chemical analysis Corchorus capsularis minerals percent protein vitamins

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jute CDPK genes and their role in stress tolerance and fiber development: A genome-wide bioinformatic investigation of Chorchorus capsularis and C. olitorius

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Plant Gene 2020年 24卷

作者： Ahmed, Borhan Alam, Mobashwer Hasan, Fakhrul Emdad, Emdadul Mannan Islam, Shahidul Rahman, Nazibur Basic and Applied Research on Jute Project Bangladesh Jute Research Institute Dhaka 1207 Bangladesh Queensland Alliance for Agriculture and Food Innovation The University of Queensland 47 Mayers Rd Nambour 4560 QLD Australia Faculty of Agriculture Patuakhali Science and Technology University Patuakhali 8802 Bangladesh Faculty of Biological Sciences Jahangirnagar University Dhaka 1342 Bangladesh

Calcium-dependent protein kinases (CDPKs) are plant-specific calcium sensors, which regulate plant growth and development and induce protective responses to environmental stresses. To date, no information on jute CDPKs is available and their uses in the genetic improvement program is underutilized. In this study, we exploited recently available genome sequence information of two jute species: Corchorus olitorius and C. capsularis to identify, characterise, and functional analysis. Using bioinformatics tools, 16 and 18 CDPK genes with serine/threonine protein kinase along with EF-hand calcium-binding domain were identified from the genomes of C. olitorius and C. capsularis, respectively. Different chromosomes harboured different CDPK genes. Four distinct clades of CDPK genes were identified by phylogenetic analysis. Protein of each clade showed higher conservation in length, structure, and presence of motif. The most prominent transcriptional responses were detected in saline and drought conditions where more than half of the CDPKs were upregulated, suggesting their important roles in abiotic stress responses of jute. Specifically, CoCDPK6, 11, 12, and their corresponding homologs CcCDPK18, 10, 8 were highly expressed in saline and drought conditions. On the other hand, CoCDPK6, 7, 11, 12, and their homologs CcCDPK18, 17, 10, 8 were highly expressed in fiber cell indicating their involvement in fiber cell development. Our results provide an important foundation for further functional dissection of CDPKs of C. olitorius and C. capsularis for salinity and drought stress adaptation and fiber quality improvement. © 2020 Elsevier B.V.

关键词： Calcium-dependent protein kinase (CDPK) Fiber development Gene expression Gene family Phylogenetic analysis Salinity and drought stress

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