[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 …
COVID-19 diagnosis: A review of rapid antigen, RT-PCR and artificial intelligence methods
As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
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 …
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 …
Feasibility of breast cancer detection through a convolutional neural network in mammographs
FM Ahmed, BS MOHAMMED - Tamjeed Journal of Healthcare …, 2023 - tamjeedpub.com
In the Iraq female samples, the malignant neoplasm type with the highest mortality rate is
breast cancer. When the disease is detected early, the success rate is higher, resulting in …
breast cancer. When the disease is detected early, the success rate is higher, resulting in …
Odors and cancer: Current status and future directions
F Gouzerh, JM Bessière, B Ujvari, F Thomas… - … et Biophysica Acta (BBA …, 2022 - Elsevier
Cancer is the second leading cause of death in the world. Because tumors detected at early
stages are easier to treat, the search for biomarkers—especially non-invasive ones—that …
stages are easier to treat, the search for biomarkers—especially non-invasive ones—that …
Characterization of abnormalities in breast cancer images using nature‐inspired metaheuristic optimized convolutional neural networks model
ON Oyelade, AE Ezugwu - Concurrency and Computation …, 2022 - Wiley Online Library
Convolutional neural networks (CNN) are deep learning models widely reported as
performing well in several image classification tasks. Training the networks for optimal …
performing well in several image classification tasks. Training the networks for optimal …
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 …
Deep learning in medical image analysis
Over recent years, deep learning (DL) has established itself as a powerful tool across a
broad spectrum of domains in imaging—eg, classification, prediction, detection …
broad spectrum of domains in imaging—eg, classification, prediction, detection …