Deep learning cascaded feature selection framework for breast cancer classification: Hybrid CNN with univariate-based approach
With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …
in the past have been solved. Effective prediction models need many normal and tumor …
A hybrid deep transfer learning of CNN-based LR-PCA for breast lesion diagnosis via medical breast mammograms
One of the most promising research areas in the healthcare industry and the scientific
community is focusing on the AI-based applications for real medical challenges such as the …
community is focusing on the AI-based applications for real medical challenges such as the …
Clinical decision support framework for segmentation and classification of brain tumor MRIs using a U-Net and DCNN cascaded learning algorithm
Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development of
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
PCDM and PCDM4MP: New Pairwise Correlation-Based Data Mining Tools for Parallel Processing of Large Tabular Datasets
The paper describes PCDM and PCDM4MP as new tools and commands capable of
exploring large datasets. They select variables based on identifying the absolute values of …
exploring large datasets. They select variables based on identifying the absolute values of …
MEM and MEM4PP: New Tools Supporting the Parallel Generation of Critical Metrics in the Evaluation of Statistical Models
This paper describes MEM and MEM4PP as new Stata tools and commands. They support
the automatic reporting and selection of the best regression and classification models by …
the automatic reporting and selection of the best regression and classification models by …
Symptom Principal Component Analysis (SPCA) for Dimensionality Reduction in Categorical Data: A Case Study on Breast Cancer
FS Al-Juboori, SA Naji, HM Sabri - National Conference on New Trends in …, 2023 - Springer
The symptom analysis is a promising technique for the expansion of a set of random
variables through linear combination over a finite field F2. From the projective space, it is …
variables through linear combination over a finite field F2. From the projective space, it is …