[HTML][HTML] Optimizing microarray cancer gene selection using swarm intelligence: Recent developments and an exploratory study

J Isuwa, M Abdullahi, YS Ali, IH Hassan… - Egyptian Informatics …, 2023 - Elsevier
Microarray data represents a valuable tool for the identification of biomarkers associated
with diseases and other biological conditions. Genes, in particular, are a type of biomarker …

A bio-inspired convolution neural network architecture for automatic breast cancer detection and classification using RNA-Seq gene expression data

TIA Mohamed, AE Ezugwu, JV Fonou-Dombeu… - Scientific Reports, 2023 - nature.com
Breast cancer is considered one of the significant health challenges and ranks among the
most prevalent and dangerous cancer types affecting women globally. Early breast cancer …

Exploring fetal brain tumor glioblastoma symptom verification with self organizing maps and vulnerability data analysis

SK Natarajan, SK Mathivanan, H Rajadurai… - Scientific Reports, 2024 - nature.com
Brain tumor glioblastoma is a disease that is caused for a child who has abnormal cells in
the brain, which is found using MRI “Magnetic Resonance Imaging” brain image using a …

An Unsupervised Deep Learning‐Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma

S Chen, Y Zang, B Xu, B Lu, R Ma… - … Methods in Medicine, 2022 - Wiley Online Library
Object. This study is aimed at constructing a deep learning architecture of the autoencoder
to integrate multiomics data and identify the risk of patients with stomach adenocarcinoma …

A Survey on AI-based Parkinson Disease Detection: Taxonomy, Case Study, and Research Challenges

S Desai, D Patel, K Patel, A Patel, NK Jadav… - … Computing: Practice and …, 2024 - scpe.org
Parkinson Disease (PD) is most common diseases from majority of disease encountered all
over the world, with more than 7 million individuals being affected. PD is a type of …

Towards Agility in Breast Cancer Treatment Principles as Adopted from Agile Software Engineering

Y Odeh, M Al-Balas - Journal of Multidisciplinary Healthcare, 2024 - Taylor & Francis
Purpose The complex nature of breast cancer demands flexible and adaptable principles
that can account for the diverse characteristics and evolving conditions of each patient …

A machine learning algorithm-based IoT-based message alert system for predicting coronary heart disease

C Dhanamjayulu, GV Suraj, M Nikhil, R Kaluri… - … on Advancements in …, 2022 - Springer
Coronary illness is one of the most dependable reasons for death in the world today. The
expectation of cardiovascular action is a basic test in the zone of clinical information …

Identifying the predictors of patient-Centered communication by machine learning methods

S Wu, X Zhang, P Chen, H Lai, Y Wu, BC Shia… - Processes, 2022 - mdpi.com
Patient-centered communication (PCC) quality is critical to increasing the quality of patient-
centered care. Based on the nationally representative data of the Health Information …

Risk Prediction Modeling for Breast Cancer using Supervised Machine Learning Approaches

T Rajendran, SA Rajathi… - 2023 2nd …, 2023 - ieeexplore.ieee.org
Millions of people worldwide are affected by breast cancer, a complicated and possibly fatal
disease. For patients to have better outcomes and have higher survival rates, early detection …

An Insight Into Viable Machine Learning Models for Early Diagnosis of Cardiovascular Disease

MMV Chalapathi, DK Vali, YVP Kumar… - … Computing: Practice and …, 2024 - scpe.org
Cardiovascular diseases (CVD) are a prominent source of death across the globe, and
these deaths are taking place in low-to middle-income nations. Due to this, CVD prevention …