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Mondal, Abhoy Chand
- A Study to Evaluate Symptoms in Essential Hypertension Using Random Forest Decision Tree Algorithm
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Authors
Affiliations
1 Department of Computer Science, The University of Burdwan, Golapbag, Burdwan-713104, IN
2 Department of Computer & Information Science, Dr. B. C. Roy Engineering College, Dugrapur-713206, IN
3 Department of Computer Science, Bagnan College, W.B., IN
1 Department of Computer Science, The University of Burdwan, Golapbag, Burdwan-713104, IN
2 Department of Computer & Information Science, Dr. B. C. Roy Engineering College, Dugrapur-713206, IN
3 Department of Computer Science, Bagnan College, W.B., IN
Source
Indian Science Cruiser, Vol 31, No 4 (2017), Pagination: 28-35Abstract
In the present study, we would like to gain the insight of the medical data through classification based data mining technique, namely random forests classification. The paper presents a hypertension risk factor symptom classification task where the decisions should be made only on the basis of general information and basis biochemical data. Even though advancements in the field of medicine make it easier to treat hypertension, there are still insufficiencies regarding the determination and evaluation of its risk factors. In this study, various risk factors used to diagnose were investigated by taking into consideration the individuals with common symptoms and complaints. Patient data were collected from a homeopathic medical practitioner. Present analysis predicts that Hypertrophy of Heart and allied, Stiffness of neck and Sensitivity to noise are most important risk symptom to predict hypertension.Keywords
Classification, Essential Hypertension, Random Forests Classifier, Confusion Matrix.References
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- A Study to Identify the Manner of Death in Head Injury Using Classification Model
Abstract Views :411 |
PDF Views:6
Authors
Affiliations
1 Department of Computer Science, The University of Burdwan, Golapbag, Burdwan- 713104, IN
2 Department of Forensic & State Medicine, Burdwan Medical College, Burdwan- 713104, IN
3 Department of Computer & Information Science, Dr. B. C. Roy Engineering College, Durgapur-713206, IN
1 Department of Computer Science, The University of Burdwan, Golapbag, Burdwan- 713104, IN
2 Department of Forensic & State Medicine, Burdwan Medical College, Burdwan- 713104, IN
3 Department of Computer & Information Science, Dr. B. C. Roy Engineering College, Durgapur-713206, IN
Source
Indian Science Cruiser, Vol 32, No 3 (2018), Pagination: 26-35Abstract
Head injury is the leading cause of death found at medico legal autopsy. This may be due to various mechanisms and thereby the nature of death in fatal head injury assumes utmost importance in forensic practice. It is often expected and hence required that a forensic pathologist apart from ascertaining the cause of death should indicate the nature of death. This has to be done on a sound scientific and objective manner as far as possible. There is need for an autopsy proven method to broadly classify the wounds into homicidal blows, accidental trauma and fall from height. The present investigation is designed to explore a classification model for identifying the nature of death from head injury.Keywords
Principal Component Analysis, Classification, Head Injuries, Burdwan Medical College, Autopsy, Eigenvalues, Forensic, Skull.References
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