Md. Shakawat Al Sakib 173-15-1650 | Daffodil International University (original) (raw)
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Papers by Md. Shakawat Al Sakib 173-15-1650
There are numerous machine learning methods that capable to develop smart automated algorithms to... more There are numerous machine learning methods that capable to develop smart automated algorithms to examine highdimensional and multi-modal biomedical dataset. This paper emphases on through clustering algorithms to advance revealing and analysis of human diseases. The mass population's disease assessment was not ever been familiar and nevertheless is an intricate procedure and necessitates a great level of competence. Numerous assessment support methods established encouraging diagnostic representations however merely an insufficient have been properly estimated in clinical surroundings. Moreover standalone decision support systems rely on profoundly on a massive volume of dataset. This research deploy unsupervised clustering approach such as K-means algorithm to build a proficient system to recognize human diseases by assessing syndromes to progress the superiority of health issues. The medical professionals and practitioners can use this smart system to corroborate the diseases diagnosis. The study is significant in health sector to reduce all kinds of diagnosis expenses.
International Journal of Advancement in Life Sciences Research, 2022
Machine Learning has a big impact on a lot of different scientific and technical disciplines, inc... more Machine Learning has a big impact on a lot of different scientific and technical disciplines, including medical research and Biophysics. Diabetes is a chronic condition marked by abnormally high glucose levels and the body's inefficient utilization of insulin. Diabetes is now becoming a leading cause of death all over the world. The objective of this article was to use multiple. Machine Learning methods are used to create a model with a limited number of dependencies, which could be used to study diabetic patients and diagnose diabetes using the PIMA dataset. Some of the most well-known prediction algorithms employed in this system are SVM (support vector machine), Multinomial Naive Bayes, Random forest, and Decision tree. Use these algorithms to construct a gathering of models by combining multiple combinations into one. This will enhance performance and accuracy.
Lecture Notes in Networks and Systems, 2022
Data Intelligence and Cognitive Informatics
There are numerous machine learning methods that capable to develop smart automated algorithms to... more There are numerous machine learning methods that capable to develop smart automated algorithms to examine highdimensional and multi-modal biomedical dataset. This paper emphases on through clustering algorithms to advance revealing and analysis of human diseases. The mass population's disease assessment was not ever been familiar and nevertheless is an intricate procedure and necessitates a great level of competence. Numerous assessment support methods established encouraging diagnostic representations however merely an insufficient have been properly estimated in clinical surroundings. Moreover standalone decision support systems rely on profoundly on a massive volume of dataset. This research deploy unsupervised clustering approach such as K-means algorithm to build a proficient system to recognize human diseases by assessing syndromes to progress the superiority of health issues. The medical professionals and practitioners can use this smart system to corroborate the diseases diagnosis. The study is significant in health sector to reduce all kinds of diagnosis expenses.
International Journal of Advancement in Life Sciences Research, 2022
Machine Learning has a big impact on a lot of different scientific and technical disciplines, inc... more Machine Learning has a big impact on a lot of different scientific and technical disciplines, including medical research and Biophysics. Diabetes is a chronic condition marked by abnormally high glucose levels and the body's inefficient utilization of insulin. Diabetes is now becoming a leading cause of death all over the world. The objective of this article was to use multiple. Machine Learning methods are used to create a model with a limited number of dependencies, which could be used to study diabetic patients and diagnose diabetes using the PIMA dataset. Some of the most well-known prediction algorithms employed in this system are SVM (support vector machine), Multinomial Naive Bayes, Random forest, and Decision tree. Use these algorithms to construct a gathering of models by combining multiple combinations into one. This will enhance performance and accuracy.
Lecture Notes in Networks and Systems, 2022
Data Intelligence and Cognitive Informatics