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COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization
The coronavirus outbreak 2019, called COVID-19, which originated in Wuhan, negatively
affected the lives of millions of people and many people died from this infection. To prevent …
affected the lives of millions of people and many people died from this infection. To prevent …
Advances in automatic identification of road subsurface distress using ground penetrating radar: State of the art and future trends
Affected by soil erosion and material deterioration, road subsurface is prone to distress such
as cavities, water-rich, and cracks. Ground penetrating radar (GPR), as a real-time …
as cavities, water-rich, and cracks. Ground penetrating radar (GPR), as a real-time …
Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction
Disease risk prediction is a rising challenge in the medical domain. Researchers have
widely used machine learning algorithms to solve this challenge. The k-nearest neighbour …
widely used machine learning algorithms to solve this challenge. The k-nearest neighbour …
Challenges in KNN classification
S Zhang - IEEE Transactions on Knowledge and Data …, 2021 - ieeexplore.ieee.org
The KNN algorithm is one of the most popular data mining algorithms. It has been widely
and successfully applied to data analysis applications across a variety of research topics in …
and successfully applied to data analysis applications across a variety of research topics in …
Coronary artery heart disease prediction: a comparative study of computational intelligence techniques
Diseases is an unusual circumstance that affects single or more parts of a human's body.
Because of lifestyle and patrimonial, different kinds of disease are increasing day by day …
Because of lifestyle and patrimonial, different kinds of disease are increasing day by day …
Automated ASD detection using hybrid deep lightweight features extracted from EEG signals
Background Autism spectrum disorder is a common group of conditions affecting about one
in 54 children. Electroencephalogram (EEG) signals from children with autism have a …
in 54 children. Electroencephalogram (EEG) signals from children with autism have a …
Digital exploration of selected heavy metals using Random Forest and a set of environmental covariates at the watershed scale
The current study was established for predicting some selected heavy metals (HMs)
including Zn, Mn, Fe, Co, Cr, Ni, and Cu, by applying random forest (RF) and a set of …
including Zn, Mn, Fe, Co, Cr, Ni, and Cu, by applying random forest (RF) and a set of …
Improved feature selection model for big data analytics
Although there are many attempts to build an optimal model for feature selection in Big Data
applications, the complex nature of processing such kind of data makes it still a big …
applications, the complex nature of processing such kind of data makes it still a big …
Quantum KNN Classification With K Value Selection and Neighbor Selection
The K-nearest neighbors (KNNs) algorithm is one of Top-10 data mining algorithms and is
widely used in various fields of artificial intelligence. This leads to that quantum KNN …
widely used in various fields of artificial intelligence. This leads to that quantum KNN …
[PDF][PDF] Identification of Triple Negative Breast Cancer Genes Using Rough Set Based Feature Selection Algorithm & Ensemble Classifier
In recent decades, microarray datasets have played an important role in triple negative
breast cancer (TNBC) detection. Microarray data classification is a challenging process due …
breast cancer (TNBC) detection. Microarray data classification is a challenging process due …