[HTML][HTML] Recurrent neural networks: A comprehensive review of architectures, variants, and applications
Recurrent neural networks (RNNs) have significantly advanced the field of machine learning
(ML) by enabling the effective processing of sequential data. This paper provides a …
(ML) by enabling the effective processing of sequential data. This paper provides a …
[HTML][HTML] Supervised machine learning in drug discovery and development: Algorithms, applications, challenges, and prospects
Drug discovery and development is a time-consuming process that involves identifying,
designing, and testing new drugs to address critical medical needs. In recent years, machine …
designing, and testing new drugs to address critical medical needs. In recent years, machine …
A survey of ensemble learning: Concepts, algorithms, applications, and prospects
Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …
machine learning applications by combining the predictions from two or more base models …
A deep learning ensemble with data resampling for credit card fraud detection
Credit cards play an essential role in today's digital economy, and their usage has recently
grown tremendously, accompanied by a corresponding increase in credit card fraud …
grown tremendously, accompanied by a corresponding increase in credit card fraud …
Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic
The COVID-19 pandemic exposed vulnerabilities in global healthcare systems and
highlighted the need for innovative, technology-driven solutions like Artificial Intelligence …
highlighted the need for innovative, technology-driven solutions like Artificial Intelligence …
A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease
SA Ebiaredoh-Mienye, TG Swart, E Esenogho… - Bioengineering, 2022 - mdpi.com
The high prevalence of chronic kidney disease (CKD) is a significant public health concern
globally. The condition has a high mortality rate, especially in developing countries. CKD …
globally. The condition has a high mortality rate, especially in developing countries. CKD …
An interpretable machine learning approach for hepatitis b diagnosis
Hepatitis B is a potentially deadly liver infection caused by the hepatitis B virus. It is a serious
public health problem globally. Substantial efforts have been made to apply machine …
public health problem globally. Substantial efforts have been made to apply machine …
SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
Abstract Background and Objective The global population has been heavily impacted by the
COVID-19 pandemic of coronavirus. Infections are spreading quickly around the world, and …
COVID-19 pandemic of coronavirus. Infections are spreading quickly around the world, and …
An improved framework for detecting thyroid disease using filter-based feature selection and stacking ensemble
In recent years, machine learning (ML) has become a pivotal tool for predicting and
diagnosing thyroid disease. While many studies have explored the use of individual ML …
diagnosing thyroid disease. While many studies have explored the use of individual ML …
Recent progress on rapid diagnosis of COVID-19 by point-of-care testing platforms
YN Tang, D Jiang, X Wang, Y Liu, D Wei - Chinese Chemical Letters, 2024 - Elsevier
The outbreak of COVID-19 has drawn great attention around the world. SARS-CoV-2 is a
highly infectious virus with occult transmission by many mutations and a long incubation …
highly infectious virus with occult transmission by many mutations and a long incubation …