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A novel classification scheme to decline the mortality rate among women due to breast tumor
Early screening of skeptical masses or breast carcinomas in mammograms is supposed to
decline the mortality rate among women. This amount can be decreased more on …
decline the mortality rate among women. This amount can be decreased more on …
Characterization of Mueller matrix elements for classifying human skin cancer utilizing random forest algorithm
Significance: The Mueller matrix decomposition method is widely used for the analysis of
biological samples. However, its presumed sequential appearance of the basic optical …
biological samples. However, its presumed sequential appearance of the basic optical …
Development and validation of a predictive radiomics model for clinical outcomes in stage I non-small cell lung cancer
Purpose To develop and validate a radiomics signature that can predict the clinical
outcomes for patients with stage I non-small cell lung cancer (NSCLC). Methods and …
outcomes for patients with stage I non-small cell lung cancer (NSCLC). Methods and …
[HTML][HTML] An effective ensemble machine learning approach to classify breast cancer based on feature selection and lesion segmentation using preprocessed …
Simple Summary The screening of breast cancer in its earlier stages can play a crucial role
in minimizing mortality rate by enabling clinicians to administer timely treatments and …
in minimizing mortality rate by enabling clinicians to administer timely treatments and …
Two-way threshold-based intelligent water drops feature selection algorithm for accurate detection of breast cancer
Breast cancer is one of the common reasons for deaths of women over the globe. It has
been found that a Computer-Aided Diagnosis (CAD) system can be designed using X-ray …
been found that a Computer-Aided Diagnosis (CAD) system can be designed using X-ray …
Covid-19 classification based on gray-level co-occurrence matrix and support vector machine
Y Chen - COVID-19: Prediction, Decision-Making, and its …, 2021 - Springer
Covid-19 is a new epidemic recently. Early diagnosis of related diseases relies on the
analysis of the patient's clinical symptoms and kit testing. To identify this disease efficiently …
analysis of the patient's clinical symptoms and kit testing. To identify this disease efficiently …
Effective mammogram classification based on center symmetric-LBP features in wavelet domain using random forests
Mammogram classification is a crucial and challenging problem, because it helps in early
diagnosis of breast cancer and supports radiologists in their decision to analyze similar …
diagnosis of breast cancer and supports radiologists in their decision to analyze similar …
Spatial Bayesian modeling of GLCM with application to malignant lesion characterization
The emerging field of cancer radiomics endeavors to characterize intrinsic patterns of tumor
phenotypes and surrogate markers of response by transforming medical images into objects …
phenotypes and surrogate markers of response by transforming medical images into objects …
Detection of breast cancer through mammogram using wavelet-based LBP features and IWD feature selection technique
Breast cancer is as one of the common reasons of deaths in women. To detect this cancer in
early stage, a computer-aided diagnosis (CAD) system can be designed using X-ray …
early stage, a computer-aided diagnosis (CAD) system can be designed using X-ray …
Detection and classification of breast cancer in mammogram images using entropy-based Fuzzy C-Means Clustering and RMCNN
Radiologists employ mammograms for the detection of breast cancer in patients, particularly
as breast cancer exhibits higher incidence rates in women. Early identification of breast …
as breast cancer exhibits higher incidence rates in women. Early identification of breast …