Reviewing ensemble classification methods in breast cancer
Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …
the same task. This approach was designed to overcome the weaknesses of single …
Data science, artificial intelligence, and machine learning: opportunities for laboratory medicine and the value of positive regulation
D Gruson, T Helleputte, P Rousseau, D Gruson - Clinical biochemistry, 2019 - Elsevier
Artificial intelligence (AI) and data science are rapidly developing in healthcare, as is their
translation into laboratory medicine. Our review article presents an overview of the data …
translation into laboratory medicine. Our review article presents an overview of the data …
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
Background Cardiovascular diseases kill approximately 17 million people globally every
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
Metaverse and healthcare: Machine learning-enabled digital twins of cancer
Medical digital twins, which represent medical assets, play a crucial role in connecting the
physical world to the metaverse, enabling patients to access virtual medical services and …
physical world to the metaverse, enabling patients to access virtual medical services and …
A deep neural network for early detection and prediction of chronic kidney disease
Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD).
Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers …
Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers …
An enhanced Predictive heterogeneous ensemble model for breast cancer prediction
S Nanglia, M Ahmad, FA Khan, NZ Jhanjhi - Biomedical Signal Processing …, 2022 - Elsevier
Breast Cancer is one of the most prevalent tumors after lung cancer and is common in both
women and men. This disease is mostly asymptomatic in the early stages thus detection is …
women and men. This disease is mostly asymptomatic in the early stages thus detection is …
A machine learning methodology for diagnosing chronic kidney disease
Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality
rate, and it induces other diseases. Since there are no obvious symptoms during the early …
rate, and it induces other diseases. Since there are no obvious symptoms during the early …
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 …
A CNN-based methodology for breast cancer diagnosis using thermal images
J Zuluaga-Gomez, Z Al Masry… - Computer Methods in …, 2021 - Taylor & Francis
ABSTRACT A recent study from GLOBOCAN disclosed that during 2018 two million women
worldwide had been diagnosed with breast cancer. Currently, mammography, magnetic …
worldwide had been diagnosed with breast cancer. Currently, mammography, magnetic …
A grey-box ensemble model exploiting black-box accuracy and white-box intrinsic interpretability
Machine learning has emerged as a key factor in many technological and scientific
advances and applications. Much research has been devoted to developing high …
advances and applications. Much research has been devoted to developing high …