Predicting breast cancer from risk factors using SVM and extra-trees-based feature selection method
Developing a prediction model from risk factors can provide an efficient method to recognize
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
[HTML][HTML] A breast cancer risk predication and classification model with ensemble learning and big data fusion
Breast cancer is a major health issue for women all over the world. Effective care and better
patient outcomes depend on early identification and precise risk prediction. Ensemble …
patient outcomes depend on early identification and precise risk prediction. Ensemble …
The study of various registration methods based on maximal stable extremal region and machine learning
This review article aims to discuss contemporary and traditional image registration methods,
which involve establishing correspondences between two or more images of a same object …
which involve establishing correspondences between two or more images of a same object …
Challenges to the Early Diagnosis of Breast Cancer: Current Scenario and the Challenges Ahead
Breast cancer is still a major problem for medical research, science, and society. Breast
cancer is the most common form of cancer among women and has a high rate of mortality …
cancer is the most common form of cancer among women and has a high rate of mortality …
Efficient breast cancer classification using LS-SVM and dimensionality reduction
AS Mohammed - Soft Computing, 2023 - Springer
Breast cancer is the main cause of cancer-related deaths among women worldwide. Several
diagnostic methods, including mammography, ultrasound, and biopsy, are used to discover …
diagnostic methods, including mammography, ultrasound, and biopsy, are used to discover …
Prediction of malaria positivity using patients' demographic and environmental features and clinical symptoms to complement parasitological confirmation before …
Background Current malaria diagnosis methods that rely on microscopy and Histidine Rich
Protein-2 (HRP2)-based rapid diagnostic tests (RDT) have drawbacks that necessitate the …
Protein-2 (HRP2)-based rapid diagnostic tests (RDT) have drawbacks that necessitate the …
TPBFS: two populations based feature selection method for medical data
H Quan, Y Zhang, Q Li, Y Liu - Cluster Computing, 2024 - Springer
The high-dimensional nature of medical data frequently results in suboptimal performance of
machine learning models. Applying feature selection before classification is necessary to …
machine learning models. Applying feature selection before classification is necessary to …
Entropy-based reliable non-invasive detection of coronary microvascular dysfunction using machine learning algorithm
X Zhao, Y Gong, L Xu, L Xia, J Zhang… - Mathematical …, 2023 - pureportal.coventry.ac.uk
Purpose: Coronary microvascular dysfunction (CMD) is emerging as an important cause of
myocardial ischemia, but there is a lack of a non-invasive method for reliable early detection …
myocardial ischemia, but there is a lack of a non-invasive method for reliable early detection …
[HTML][HTML] The role of aspirin in with breast cancer patients receiving neoadjuvant chemotherapy by targeting JAK2/STAT3
Y Zheng, H Tang, Q Zheng, D Guan, Q Mo - Journal of Radiation Research …, 2023 - Elsevier
What is known and objective Neoadjuvant chemotherapy refers to systemic chemotherapy
before implementing local treatment methods such as surgery or radiotherapy, and …
before implementing local treatment methods such as surgery or radiotherapy, and …
GA-SVM Wrapper Feature Selection untuk Penanganan Data Berdimensi Tinggi
Peningkatan data dalam beberapa tahun terakhir ini mengalami peningkatan yang sangat
signifikan karena penggunaan sosial media dan peralihan menjadi era digital. Teknik untuk …
signifikan karena penggunaan sosial media dan peralihan menjadi era digital. Teknik untuk …