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 …
Scientometric analysis of artificial intelligence (AI) for geohazard research
S Jiang, J Ma, Z Liu, H Guo - Sensors, 2022 - mdpi.com
Geohazard prevention and mitigation are highly complex and remain challenges for
researchers and practitioners. Artificial intelligence (AI) has become an effective tool for …
researchers and practitioners. Artificial intelligence (AI) has become an effective tool for …
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 …
[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 …
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 …
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 …
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 …
A representation coefficient-based k-nearest centroid neighbor classifier
K-nearest neighbor rule (KNN) has been regarded as one of the top 10 methods in the field
of data mining. Due to its simplicity and effectiveness, it has been widely studied and applied …
of data mining. Due to its simplicity and effectiveness, it has been widely studied and applied …
[HTML][HTML] A new COVID-19 detection method from human genome sequences using CpG island features and KNN classifier
Various viral epidemics have been detected such as the severe acute respiratory syndrome
coronavirus and the Middle East respiratory syndrome coronavirus in the last two decades …
coronavirus and the Middle East respiratory syndrome coronavirus in the last two decades …