[HTML][HTML] RNN and biLSTM fusion for accurate automatic epileptic seizure diagnosis using EEG signals

NA Samee, NF Mahmoud, EA Aldhahri, A Rafiq… - Life, 2022 - mdpi.com
Epilepsy is a common neurological condition. The effects of epilepsy are not restricted to
seizures alone. They comprise a wide spectrum of problems that might impair and reduce …

Breast Cancer-Risk Factors and Prediction Using Machine-Learning Algorithms and Data Source: A Review of Literature

A Alsabry, M Algabri, AM Ahsan - Sana'a University Journal of …, 2023 - journals.su.edu.ye
Breast cancer (BC) is a major health concern worldwide. It is a complex and multifactorial
disease, and identifying its risk factors is crucial for early detection and effective treatment …

[HTML][HTML] 5G-based telerobotic ultrasound system improves access to breast examination in rural and remote areas: A prospective and two-scenario study

T He, YY Pu, YQ Zhang, ZB Qian, LH Guo, LP Sun… - Diagnostics, 2023 - mdpi.com
Objective: Ultrasound (US) plays an important role in the diagnosis and management of
breast diseases; however, effective breast US screening is lacking in rural and remote …

Development of an expert-level right ventricular abnormality detection algorithm based on deep learning

Z Liu, H Li, W Li, F Zhang, W Ouyang, S Wang… - Interdisciplinary …, 2023 - Springer
Purpose Studies relating to the right ventricle (RV) are inadequate, and specific diagnostic
algorithms still need to be improved. This essay is designed to make exploration and …

[HTML][HTML] Automatic tumor identification from scans of histopathological tissues

M Kundrotas, E Mažonienė, D Šešok - Applied Sciences, 2023 - mdpi.com
Latest progress in development of artificial intelligence (AI), especially machine learning
(ML), allows to develop automated technologies that can eliminate or at least reduce human …

Improved Breast Cancer Detection in Mammography Images: Integration of Convolutional Neural Network and Local Binary Pattern Approach

OJ Awujoola, TE Aniemeka, FN Ogwueleka… - … Algorithms Using Scikit …, 2024 - igi-global.com
Cancer, characterized by uncontrolled cell division, is an incurable ailment, with breast
cancer being the most prevalent form globally. Early detection remains critical in reducing …

Breast Cancer Detection Based DenseNet with Attention Model in Mammogram Images

TE Mousa, R Zouari, M Baklouti - International Conference on Model and …, 2023 - Springer
Breast cancer has become a very interesting topic due to the massive number of deaths
among women across the world. Radiologists can diagnose breast cancer faster and more …

Malaria Disease Prediction Based on Convolutional Neural Networks

DAL Kafaf, NN Thamir… - Journal of Applied …, 2024 - journal.yrpipku.com
This study delves into the investigation of the efficacy of Convolutional Neural Networks
(CNNs) in identifying malaria through the examination of cell images. The dataset employed …

深度学习在乳腺癌影像学检查中的应用进展.

王一凡, 刘静, 马金刚, 邵润华… - Journal of Frontiers of …, 2024 - search.ebscohost.com
乳腺癌是女性最常见的恶性肿瘤, 其早期发现具有决定性意义. 乳腺影像学检查在早期发现乳腺
癌以及在治疗期间监测与评估方面发挥着重要作用, 但人工检测医学影像通常耗时耗力. 最近 …

Evaluating the Robustness of Neural Networks Against Adversarial Perturbations

CR Bhat, J Nandhini, S Narayanasamy… - … Security and Artificial …, 2023 - ieeexplore.ieee.org
N eural networks have impressive powers in the field of deep learning and have been used
in many different applications. Nevertheless, the issue of robustness against deliberate …