Browsing by Author "Chakraborty, Setu"

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Anticipation of the Significance of Risk Factors in Cervical Cancer for Low Incoming Country: Bangladesh Perspective
(Researchgate, 2015-11) Asaduzzaman, Sayed; Ahmed, Kawsar; Chakraborty, Setu; Hossain, Md. Goljar; Bashar, Mamun Ibn; Bhuiyan, Touhid; Chandan, Subrata Sarker
Cervical cancer is the second alarming cancer for women of low incoming countries like Bangladesh. In future it would be the main cause of death of Bangladeshi women by caner. To find the significant factors, association among them and making a precedence list among them by data mining and statistical approaches. During, February 2014 till July 2014 a case-control study has been acquitted on 436 participants of both patients (199) and non-patients (237). Using an accurate questionnaire based on previous study the whole data collection process done in the different part of the Dhaka cities and diagnostic center. About 10 factors like first sex at the age below 16, Lack of knowledge about cervical cancer, number of children above 3, STI (Sexually Transmitted Infection) affection, previous cervical cancer history are founded highly significant by the statistical analysis and later those factors were given precedence by data mining process Ranker algorithm with different attribute evaluator. Oral contraception taken, contraception used and vaccine taken factors are lower significant than the other factors by the analysis. Both data mining and statistical approaches depict a comparative analysis and by the result the significant factors and the significance priority can be measured. Full Text Link: http://doi.org/10.14299/ijser.2015.11.009
Hazardous consequences of polygamy, contraceptives and number of childs on cervical cancer in a low incoming country: Bangladesh
(Cumhuriyet Üniversitesi Fen Fakültesi, 2016-02-18) Asaduzzaman, Sayed; Chakraborty, Setu; Hossain, Md. Goljar; Bashar, Mamun Ibn; Bhuiyan, Touhid; Paul, Bikash Kumar; Chandan, Subrata Sarker; Ahmad, Kawsar
Cervical cancer is the one of the most alarming disease among female in the low incoming country like Bangladesh. The societies of Bangladesh are conservative because of lacking education and consciousness. The information on Bangladeshi female’s cervical cancer factors is not available. Purpose: To retrieve the associations among the factors with cervical cancer and to raise awareness among the women of society. Methods: A case-control study has been acquitted on 426 participants of both patients and non-patients from February 2014 till July 2014. Through a precise questionnaire based on former study the whole data collection process done. For analyzing of data some tasks like binary logistic regression, odds ratio, crosstabs and p-value tests have executed. Results: Factors like First sex at the age below 16, Lack of knowledge about cervical cancer, number of children above 3, STI (Sexually Transmitted Infection) affection, previous cervical cancer history are founded highly significant on the other hand oral contraception taken, contraception used and vaccine taken factors are significantly lower than the previous factors. Conclusions: The analysis would help to predict the risk factors of the cervical cancer and may help to diminish the cancer not only from Bangladesh but all over the world. Full Text Link: http://dx.doi.org/10.17776/csj.04592
Machine Learning to Reveal an Astute Risk Predictive Framework for Gynecologic Cancer and Its Impact on Women Psychology
(BMC Bioinformatics, Springer, 2021-04-24) Asaduzzaman, Sayed; Ahmed, Md. Raihan; Rehana, Hasin; Chakraborty, Setu; Islam, Md. Shariful; Bhuiyan, Touhid
Background In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress. Results For functioning factors and subfactors, several machine learning models like Logistics Regression, Random Forest, AdaBoost, Naïve Bayes, Neural Network, kNN, CN2 rule Inducer, Decision Tree, Quadratic Classifier were compared with standard metrics e.g., F1, AUC, CA. For certainty info gain, gain ratio, gini index were revealed for both cervical and ovarian cancer. Attributes were ranked using different feature selection evaluators. Then the most significant analysis was made with the significant factors. Factors like children, age of first intercourse, age of husband, Pap test, age are the most significant factors of cervical cancer. On the other hand, genital area infection, pregnancy problems, use of drugs, abortion, and the number of children are important factors of ovarian cancer. Conclusion Resulting factors were merged, categorized, weighted according to their significance level. The categorized factors were indexed using ranker algorithm which provides them a weightage value. An algorithm has been formulated afterward which can be used to predict the risk level of cervical and ovarian cancer in relation to women's mental health. The research will have a great impact on the low incoming country like Bangladesh as most women in low incoming nations were unaware of it. As these two can be described as the most sensitive cancers to women, the development of the application from algorithm will also help to reduce women’s mental stress. More data and parameters will be added in future for research in this perspective.