Search Results - "Ghosh, Soumadip"

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  1. 1

    An Efficient Computational Risk Prediction Model of Heart Diseases Based on Dual-Stage Stacked Machine Learning Approaches by Mondal, Subhash, Maity, Ranjan, Omo, Yachang, Ghosh, Soumadip, Nag, Amitava

    Published in IEEE access (2024)
    “…Cardiovascular diseases (CVDs) continue to be a prominent cause of global mortality, necessitating the development of effective risk prediction models to…”
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    Journal Article
  2. 2

    Brain stroke prediction model based on boosting and stacking ensemble approach by Mondal, Subhash, Ghosh, Soumadip, Nag, Amitava

    “…The concern of brain stroke increases rapidly in young age groups daily. The leading causes of death from stroke globally will rise to 6.7 million yearly if…”
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    Journal Article
  3. 3

    3PNMF-MKL: A non-negative matrix factorization-based multiple kernel learning method for multi-modal data integration and its application to gene signature detection by Mallik, Saurav, Sarkar, Anasua, Nath, Sagnik, Maulik, Ujjwal, Das, Supantha, Pati, Soumen Kumar, Ghosh, Soumadip, Zhao, Zhongming

    Published in Frontiers in genetics (14-02-2023)
    “…In this current era, biomedical big data handling is a challenging task. Interestingly, the integration of multi-modal data, followed by significant feature…”
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    Journal Article
  4. 4

    Evaluation and Optimization of Biomedical Image-Based Deep Convolutional Neural Network Model for COVID-19 Status Classification by Ghosh, Soumadip, Banerjee, Suharta, Das, Supantha, Hazra, Arnab, Mallik, Saurav, Zhao, Zhongming, Mukherji, Ayan

    Published in Applied sciences (01-11-2022)
    “…Accurate detection of an individual’s coronavirus disease 2019 (COVID-19) status has become critical as the COVID-19 pandemic has led to over 615 million cases…”
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    Journal Article
  5. 5

    A novel Neuro-fuzzy classification technique for data mining by Ghosh, Soumadip, Biswas, Sushanta, Sarkar, Debasree, Sarkar, Partha Pratim

    Published in Egyptian informatics journal (01-11-2014)
    “…In our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The inputs to the Neuro-fuzzy classification system were fuzzified by…”
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    Journal Article
  6. 6

    DeMoS: dense module based gene signature detection through quasi-clique: an application to cervical cancer prognosis by Saha, Suparna, Seth, Soumita, Ghosh, Soumadip, Qin, Guimin, Bhadra, Tapas, Pati, Soumen Kumar, Chakraborty, Somenath, Mallik, Saurav

    “…Nowadays, cervical cancer is a leading cause of death among women. Determining the gene signature is one of the major issues in bioinformatics. Though many of…”
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    Journal Article
  7. 7

    Soil Classification From Large Imagery Databases Using a Neuro-Fuzzy Classifier by Ghosh, Soumadip, Biswas, Debasish, Biswas, Sushanta, Chanda Sarkar, Debasree, Sarkar, Partha Pratim

    “…In this paper, we propose a neuro-fuzzy (NF) classification technique to determine various soil classes from large imagery soil databases. The technique looks…”
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    Journal Article
  8. 8

    On Label Languages of Homogeneous Variant of SNPSSP (HSNPSSP) by Paul, Prithwineel, Ghosh, Soumadip

    “…In this paper, we investigate the family of languages generated by the labels of the homogeneous variant of spiking neural P systems with structural plasticity…”
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    Conference Proceeding
  9. 9
  10. 10

    Watson-Crick grammar and its label languages by Paul, Prithwineel, Ghosh, Soumadip, Mandal, Arpita

    “…DNA molecules are the building blocks of life. In the last few decades, the fields of biotechnology and molecular biology have made significant progress…”
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    Conference Proceeding
  11. 11

    Early Prediction of Coronary Heart Disease using Boosting-based Voting Ensemble Learning by Mondal, Subhash, Maity, Ranjan, Singh, Yash Raj, Ghosh, Soumadip, Nag, Amitava

    “…Coronary-Heart-Disease (CHD) risk increases daily due to the uncontrolled lifestyle of today's adult age group. The early detection of the disease can prevent…”
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    Conference Proceeding
  12. 12

    Thyroid Disease Prediction Model on Boosting-based Stacking Ensemble Approach by Mondal, Subhash, Dutta, Souptik, Ghosh, Soumadip, Gupta, Sarbartha, Kakati, Dhrubajit, Nag, Amitava

    “…The thyroid gland plays a significant role in the human body's metabolism, growth, and development. Though it is not a life-threatening disease, a person…”
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    Conference Proceeding
  13. 13

    A comparative study of breast cancer detection based on SVM and MLP BPN classifier by Ghosh, Soumadip, Mondal, Sujoy, Ghosh, Bhaskar

    “…The breast cancer is a severe disease found among females all over the world. This is a type of cancer disease arising from human breast tissue cells, usually…”
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    Conference Proceeding
  14. 14

    Detection of Chronic Kidney Disease Using Neuro-Fuzzy Rule-based Classifier by Das, Supantha, Hazra, Arnab, Pati, Soumen Kumar, Ghosh, Soumadip, Mallik, Saurav, Banerjee, Suharta, Mukherji, Ayan, Li, Aimin, Zhao, Zhongming

    “…Chronic kidney disease (CKD) is as severe as cancer in today s world. It may even lead to the permanent failure of kidney. The initial detection of this…”
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    Conference Proceeding
  15. 15

    Association rule mining algorithms and Genetic Algorithm: A comparative study by Ghosh, S., Biswas, S., Sarkar, D., Sarkar, P. P.

    “…Generally frequent itemsets are extracted from large databases by applying association rule mining (ARM) algorithms like Apriori, Partition, Pincer-Search,…”
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    Conference Proceeding
  16. 16

    Mining Frequent Itemsets Using Genetic Algorithm by Ghosh, Soumadip, Biswas, Sushanta, Sarkar, Debasree, Sarkar, Partha Pratim

    Published 01-11-2010
    “…International Journal of Artificial Intelligence & Applications (IJAIA), Vol.1, No.4, October 2010 In general frequent itemsets are generated from large data…”
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    Journal Article
  17. 17

    Weather Data Mining using Artificial Neural Network by Ghosh, S., Nag, A., Biswas, D., Singh, J. P., Biswas, S., Sarkar, D., Sarkar, P. P.

    “…Weather Data Mining is a form of Data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information…”
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    Conference Proceeding