141_56.4_Mehedi Hasan Shakil - Academia.edu (original) (raw)

Papers by 141_56.4_Mehedi Hasan Shakil

Research paper thumbnail of Survey on Perception of People Regarding Utilization of Computer Science & Information Technology in Manipulation of Big Data, Disease Detection & Drug Discovery

this research explores the manipulation of biomedical big data and diseases detection using autom... more this research explores the manipulation of biomedical big data and diseases detection using automated computing mechanisms. As efficient and cost effective way to discover disease and drug is important for a society so computer aided automated system is a must. This paper aims to understand the importance of computer aided automated system among the people. The analysis result from collected data contributes to finding an effective result that people have enough understanding and much better knowledge about big data and computer aided automated system. moreover, perspective and trustworthiness of people regarding recent advancement of computer aided technologies in biomedical science have been demonstrated in this research. however, appearance of big data in the field of medical science and manipulation of those data have been concentrated on this research. Finally suggestions have been developed for further research related to computer technology in manipulation of big data, diseas...

Research paper thumbnail of A Deep Learning Based Classification Model for the Detection of Brain Tumor using MRI

International Journal of Research and Innovation in Applied Science

The diagnosis of a brain tumor requires high accuracy, as even small errors in judgment can lead ... more The diagnosis of a brain tumor requires high accuracy, as even small errors in judgment can lead to critical problems. For this reason, brain tumor segmentation is an important challenge for medical purposes. The wrong classification can lead to worse consequences. Therefore, these must be properly divided into many classes or levels, and this is where multiclass classification comes into play. The latest development of image classification technology has made great progress, and the most popular and better method is considered to be the best in this area is CNN, so this paper uses CNN for the brain tumor classification problem. The proposed model successfully classifies brain images into two distinct categories, namely the absence of tumors indicating that a given brain MRI is free of tumors or the Brain contains Tumor. This model produces an accuracy based on the results of a study that was conducted on a group of volunteers.

Research paper thumbnail of Categorization of Customer Preference and Process of Logo Design

Research paper thumbnail of Distribution of the ratio of Maxwell and Rice random variables

International Journal of Contemporary Mathematical Sciences, 2006

The distributions of the ratio of independent random variables arise in many applied problems. Th... more The distributions of the ratio of independent random variables arise in many applied problems. These have been extensively studied by many researchers. In this paper, the distribution of the ratio Y X has been derived when X and Y are Maxwell and Rice random variables and are distributed independently of each other. The associated pdfs, cdfs, and kth moments have been given.

Research paper thumbnail of Diabetes Prediction in Healthcare at Early Stage Using Machine Learning Approach

2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021

Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by t... more Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by this disease. In line with the growing morbidness in the last few years, 642 million people can be infected with diabetes within 2040 which is one among 10 individuals. So undoubtedly this malady needs more attention. Nowadays the usage of machine learning is increasing. So, in many medical perspectives, this technique has been utilized. We have chosen methodologies that give the best performances for independent testing to confirm the universal applicability of the techniques. We have focused on early detecting this disease. We have collected data from Khulna Diabetes Center at Khulna where the instances is 289 and 13 features. In our study, we use the Logistic Regression model with 88%, XGboost 86.36% and Random Forest with 86.36% accuracy. We found that the random forest model performs the best output for diabetics detection.

Research paper thumbnail of Survey on Perception of People Regarding Utilization of Computer Science & Information Technology in Manipulation of Big Data, Disease Detection & Drug Discovery

this research explores the manipulation of biomedical big data and diseases detection using autom... more this research explores the manipulation of biomedical big data and diseases detection using automated computing mechanisms. As efficient and cost effective way to discover disease and drug is important for a society so computer aided automated system is a must. This paper aims to understand the importance of computer aided automated system among the people. The analysis result from collected data contributes to finding an effective result that people have enough understanding and much better knowledge about big data and computer aided automated system. moreover, perspective and trustworthiness of people regarding recent advancement of computer aided technologies in biomedical science have been demonstrated in this research. however, appearance of big data in the field of medical science and manipulation of those data have been concentrated on this research. Finally suggestions have been developed for further research related to computer technology in manipulation of big data, diseas...

Research paper thumbnail of A Deep Learning Based Classification Model for the Detection of Brain Tumor using MRI

International Journal of Research and Innovation in Applied Science

The diagnosis of a brain tumor requires high accuracy, as even small errors in judgment can lead ... more The diagnosis of a brain tumor requires high accuracy, as even small errors in judgment can lead to critical problems. For this reason, brain tumor segmentation is an important challenge for medical purposes. The wrong classification can lead to worse consequences. Therefore, these must be properly divided into many classes or levels, and this is where multiclass classification comes into play. The latest development of image classification technology has made great progress, and the most popular and better method is considered to be the best in this area is CNN, so this paper uses CNN for the brain tumor classification problem. The proposed model successfully classifies brain images into two distinct categories, namely the absence of tumors indicating that a given brain MRI is free of tumors or the Brain contains Tumor. This model produces an accuracy based on the results of a study that was conducted on a group of volunteers.

Research paper thumbnail of Categorization of Customer Preference and Process of Logo Design

Research paper thumbnail of Distribution of the ratio of Maxwell and Rice random variables

International Journal of Contemporary Mathematical Sciences, 2006

The distributions of the ratio of independent random variables arise in many applied problems. Th... more The distributions of the ratio of independent random variables arise in many applied problems. These have been extensively studied by many researchers. In this paper, the distribution of the ratio Y X has been derived when X and Y are Maxwell and Rice random variables and are distributed independently of each other. The associated pdfs, cdfs, and kth moments have been given.

Research paper thumbnail of Diabetes Prediction in Healthcare at Early Stage Using Machine Learning Approach

2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021

Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by t... more Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by this disease. In line with the growing morbidness in the last few years, 642 million people can be infected with diabetes within 2040 which is one among 10 individuals. So undoubtedly this malady needs more attention. Nowadays the usage of machine learning is increasing. So, in many medical perspectives, this technique has been utilized. We have chosen methodologies that give the best performances for independent testing to confirm the universal applicability of the techniques. We have focused on early detecting this disease. We have collected data from Khulna Diabetes Center at Khulna where the instances is 289 and 13 features. In our study, we use the Logistic Regression model with 88%, XGboost 86.36% and Random Forest with 86.36% accuracy. We found that the random forest model performs the best output for diabetics detection.