Statistical normalization methods in microbiome data with application to microbiome cancer research
Y Xia - Gut Microbes, 2023 - Taylor & Francis
Mounting evidence has shown that gut microbiome is associated with various cancers,
including gastrointestinal (GI) tract and non-GI tract cancers. But microbiome data have …
including gastrointestinal (GI) tract and non-GI tract cancers. But microbiome data have …
Advanced meta-heuristic algorithm based on Particle Swarm and Al-biruni Earth Radius optimization methods for oral cancer detection
Oral cancer is a deadly form of cancerous tumor that is widely spread in low and middle-
income countries. An early and affordable oral cancer diagnosis might be achieved by …
income countries. An early and affordable oral cancer diagnosis might be achieved by …
[HTML][HTML] Deep learning approaches for cyberbullying detection and classification on social media
S Neelakandan, M Sridevi… - Computational …, 2022 - ncbi.nlm.nih.gov
As a result of the ease with which the internet and cell phones can be accessed, online
social networks (OSN) and social media have seen a significant increase in popularity in …
social networks (OSN) and social media have seen a significant increase in popularity in …
Anomaly detection in 6G networks using machine learning methods
While the cloudification of networks with a micro-services-oriented design is a well-known
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
Fused weighted federated deep extreme machine learning based on intelligent lung cancer disease prediction model for healthcare 5.0
In the era of advancement in information technology and the smart healthcare industry 5.0,
the diagnosis of human diseases is still a challenging task. The accurate prediction of …
the diagnosis of human diseases is still a challenging task. The accurate prediction of …
Machine learning-based anomaly detection using K-mean array and sequential minimal optimization
Recently, artificial intelligence (AI) techniques have been used to describe the
characteristics of information, as they help in the process of data mining (DM) to analyze …
characteristics of information, as they help in the process of data mining (DM) to analyze …
[Retracted] Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms
P Ajay, B Nagaraj, R Huang… - Contrast Media & …, 2022 - Wiley Online Library
Intelligent machines have grown in importance in recent years in object recognition in terms
of their ability to envision, comprehend, and reach decisions. There are a lot of complicated …
of their ability to envision, comprehend, and reach decisions. There are a lot of complicated …
Empirical study on classifiers for earlier prediction of COVID-19 infection cure and death rate in the Indian states
Machine Learning methods can play a key role in predicting the spread of respiratory
infection with the help of predictive analytics. Machine Learning techniques help mine data …
infection with the help of predictive analytics. Machine Learning techniques help mine data …
MERGE: A model for multi-input biomedical federated learning
Driven by the deep learning (DL) revolution, artificial intelligence (AI) has become a
fundamental tool for many biomedical tasks, including analyzing and classifying diagnostic …
fundamental tool for many biomedical tasks, including analyzing and classifying diagnostic …
MLP-like model with convolution complex transformation for auxiliary diagnosis through medical images
Medical images such as facial and tongue images have been widely used for intelligence-
assisted diagnosis, which can be regarded as the multi-label classification task for disease …
assisted diagnosis, which can be regarded as the multi-label classification task for disease …