Deep learning models for disease-associated circRNA prediction: a review
Emerging evidence indicates that circular RNAs (circRNAs) can provide new insights and
potential therapeutic targets for disease diagnosis and treatment. However, traditional …
potential therapeutic targets for disease diagnosis and treatment. However, traditional …
Artificial intelligence techniques for predictive modeling of vector-borne diseases and its pathogens: a systematic review
Vector-borne diseases (VBDs) have a significant impact on human and animal health. VBD
has been emerging or re-emerging in a variety of geographic regions, raising alarming new …
has been emerging or re-emerging in a variety of geographic regions, raising alarming new …
Classification based on decision tree algorithm for machine learning
B Charbuty, A Abdulazeez - Journal of Applied Science and Technology …, 2021 - jastt.org
Decision tree classifiers are regarded to be a standout of the most well-known methods to
data classification representation of classifiers. Different researchers from various fields and …
data classification representation of classifiers. Different researchers from various fields and …
A novel community detection based genetic algorithm for feature selection
The feature selection is an essential data preprocessing stage in data mining. The core
principle of feature selection seems to be to pick a subset of possible features by excluding …
principle of feature selection seems to be to pick a subset of possible features by excluding …
Machine learning-based IoT system for COVID-19 epidemics
The planet earth has been facing COVID-19 epidemic as a challenge in recent time. It is
predictable that the world will be fighting the pandemic by taking precautions steps before …
predictable that the world will be fighting the pandemic by taking precautions steps before …
Artificial intelligence algorithm comparison and ranking for weight prediction in sheep
A Hamadani, NA Ganai - Scientific Reports, 2023 - nature.com
In a rapidly transforming world, farm data is growing exponentially. Realizing the importance
of this data, researchers are looking for new solutions to analyse this data and make farming …
of this data, researchers are looking for new solutions to analyse this data and make farming …
Optimized hybrid investigative based dimensionality reduction methods for malaria vector using KNN classifier
MO Arowolo, MO Adebiyi, AA Adebiyi, O Olugbara - Journal of Big Data, 2021 - Springer
RNA-Seq data are utilized for biological applications and decision making for the
classification of genes. A lot of works in recent time are focused on reducing the dimension …
classification of genes. A lot of works in recent time are focused on reducing the dimension …
Classification of malaria cell image using inception-v3 architecture
Malaria is a severe global public health problem caused by the bite of infected mosquitoes. It
can be cured, but only with early detection and effective, quick treatment. It can cause severe …
can be cured, but only with early detection and effective, quick treatment. It can cause severe …
Analyzing and minimizing the effects of Vector-borne diseases using machine and deep learning techniques: A systematic review
Among the numerous threats facing our world, Vector-borne illnesses pose the greatest
threat. Although arboviruses have a long history of infecting humans, they have recently …
threat. Although arboviruses have a long history of infecting humans, they have recently …
The use of knowledge extraction in predicting customer churn in B2B
AA Jamjoom - Journal of Big Data, 2021 - Springer
Data mining techniques were used to investigate the use of knowledge extraction in
predicting customer churn in insurance companies. Data were included from a health …
predicting customer churn in insurance companies. Data were included from a health …