Automated stratification of liver disease in ultrasound: an online accurate feature classification paradigm
Purpose Fatty liver disease (FLD) is one of the most common diseases in liver. Early
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …
Mammography classification using modified hybrid SVM-KNN
Today leading cause of cancer deaths for women is the Breast cancer. For early and
accurate detection of breast cancer, mammography is found to be the most reliable and …
accurate detection of breast cancer, mammography is found to be the most reliable and …
Organ-based medical image classification using support vector machine
MY Khachane - International Journal of Synthetic Emotions (IJSE), 2017 - igi-global.com
Abstract Computer-Aided Detection/Diagnosis (CAD) through artificial Intelligence is
emerging ara in Medical Image processing and health care to make the expert systems …
emerging ara in Medical Image processing and health care to make the expert systems …
An ensemble shape gradient features descriptor based nodule detection paradigm: a novel model to augment complex diagnostic decisions assistance
Primarily, there are three basic operational constituents of Nodule Detection Systems
namely nodule candidate detection, classification of nodule and extraction of features …
namely nodule candidate detection, classification of nodule and extraction of features …
Classification of breast tissue as normal or abnormal based on texture analysis of digital mammogram
FB Garma, MA Hassan - Journal of Medical Imaging and Health …, 2014 - ingentaconnect.com
The breast cancer is a serious public health problem among women in the world. Efforts in
Computer Vision have been made in order to improve the diagnostic accuracy by …
Computer Vision have been made in order to improve the diagnostic accuracy by …
[PDF][PDF] Outlier detection with enhanced angle-based outlier factor in high-dimensional data stream
Z Shou, H Tian, S Li, F Zou - Int. J. Innov. Comput. Inf. Control, 2018 - ijicic.org
Outlier detection over data stream is an increasingly important research in many fields.
Traditional methods are no longer applicable. In this paper, a novel outlier detection …
Traditional methods are no longer applicable. In this paper, a novel outlier detection …
A deep classification system for medical data analysis
AM Hassan, YF Hassan… - Journal of Medical …, 2018 - ingentaconnect.com
Medical records encompass entities representing patients' vital aspects. Whenever
incorporated, entities assist in building up a comprehensive diagnosis of the patient …
incorporated, entities assist in building up a comprehensive diagnosis of the patient …
Mammogram classification using extreme learning machine and genetic programming
K Menaka, S Karpagavalli - 2014 International Conference on …, 2014 - ieeexplore.ieee.org
Mammogram is an x-ray examination of breast. It is used to detect and diagnose breast
disease in women who either have breast problems such as a lump, pain or nipple …
disease in women who either have breast problems such as a lump, pain or nipple …
[PDF][PDF] Outlier detection based on density of hypercube in high-dimensional data stream
Z Shou, F Zou, S Li, X Lu - Int. J. Innov. Comput. Inf. Control, 2019 - ijicic.org
Outlier detection over data stream is an increasingly important task in data mining.
Moreover, high-dimensional data stream is becoming increasingly ubiquitous in many fields …
Moreover, high-dimensional data stream is becoming increasingly ubiquitous in many fields …
[PDF][PDF] International Journal of Innovative Computing, Information and Control
Outlier detection over data stream is an increasingly important research in many fields.
Traditional methods are no longer applicable. In this paper, a novel outlier detection …
Traditional methods are no longer applicable. In this paper, a novel outlier detection …