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Papers by pranjali kasture
2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)
International Journal of Computer Trends and Technology, Jul 25, 2021
Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an... more Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an early stage as it doesn't show too many symptoms. The proposed work is to develop and validate predictive models for the progression of CKD. The main outcome of this is to measure kidney failure, defined as the need for dialysis or pre-emptive kidney transplantation. The model will suggest the patient the way to maintain a healthy lifestyle as well as facilitate the doctor to visually represent the risk and severity of the disease and how to go about the future treatment.
IJCTT Journal, 2021
Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an... more Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an early stage as it doesn't show too many symptoms. The proposed work is to develop and validate predictive models for the progression of CKD. The main outcome of this is to measure kidney failure, defined as the need for dialysis or pre-emptive kidney transplantation. The model will suggest the patient the way to maintain a healthy lifestyle as well as facilitate the doctor to visually represent the risk and severity of the disease and how to go about the future treatment.
International Journal of Computer Applications, Nov 15, 2012
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect ... more Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and remove anomalous objects from data.mining. The proposed approach to detect outlier includes three methods which are clustering, pruning and computing outlier score. For clustering k-means algorithm is used which partition the dataset into given number of clusters. In pruning, based on some distance measure, points which are closed to centroid of each cluster are pruned. For the unpruned points, local distance based outlier factor (LDOF) measure is calculated. A measure called LDOF, tells how much a point is deviating from its neighbors. The high LDOF value of a point indicates that the point is deviating more from its neighbors and probably it may be an outlier.
2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)
International Journal of Computer Trends and Technology, Jul 25, 2021
Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an... more Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an early stage as it doesn't show too many symptoms. The proposed work is to develop and validate predictive models for the progression of CKD. The main outcome of this is to measure kidney failure, defined as the need for dialysis or pre-emptive kidney transplantation. The model will suggest the patient the way to maintain a healthy lifestyle as well as facilitate the doctor to visually represent the risk and severity of the disease and how to go about the future treatment.
IJCTT Journal, 2021
Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an... more Chronic kidney disease (CKD) is a common yet deadly disease that can be difficult to detect at an early stage as it doesn't show too many symptoms. The proposed work is to develop and validate predictive models for the progression of CKD. The main outcome of this is to measure kidney failure, defined as the need for dialysis or pre-emptive kidney transplantation. The model will suggest the patient the way to maintain a healthy lifestyle as well as facilitate the doctor to visually represent the risk and severity of the disease and how to go about the future treatment.
International Journal of Computer Applications, Nov 15, 2012
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect ... more Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and remove anomalous objects from data.mining. The proposed approach to detect outlier includes three methods which are clustering, pruning and computing outlier score. For clustering k-means algorithm is used which partition the dataset into given number of clusters. In pruning, based on some distance measure, points which are closed to centroid of each cluster are pruned. For the unpruned points, local distance based outlier factor (LDOF) measure is calculated. A measure called LDOF, tells how much a point is deviating from its neighbors. The high LDOF value of a point indicates that the point is deviating more from its neighbors and probably it may be an outlier.