Predicting colorectal cancer using machine and deep learning algorithms: Challenges and opportunities

D Alboaneen, R Alqarni, S Alqahtani… - Big Data and Cognitive …, 2023 - mdpi.com
One of the three most serious and deadly cancers in the world is colorectal cancer. The most
crucial stage, like with any cancer, is early diagnosis. In the medical industry, artificial …

A dependable hybrid machine learning model for network intrusion detection

MA Talukder, KF Hasan, MM Islam, MA Uddin… - Journal of Information …, 2023 - Elsevier
Network intrusion detection systems (NIDSs) play an important role in computer network
security. There are several detection mechanisms where anomaly-based automated …

[HTML][HTML] An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning

MA Talukder, MM Islam, MA Uddin, A Akhter… - Expert systems with …, 2023 - Elsevier
Brain tumors are among the most fatal and devastating diseases, often resulting in
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …

Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey

MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …

[HTML][HTML] Robust clinical applicable CNN and U-Net based algorithm for MRI classification and segmentation for brain tumor

A Akter, N Nosheen, S Ahmed, M Hossain… - Expert Systems with …, 2024 - Elsevier
Early diagnosis of brain tumors is critical for enhancing patient prognosis and treatment
options, while accurate classification and segmentation of brain tumors are vital for …

[HTML][HTML] A robust hybrid machine learning model for Bengali cyber bullying detection in social media

A Akhter, UK Acharjee, MA Talukder, MM Islam… - Natural Language …, 2023 - Elsevier
Social networking platforms give users countless opportunities to share information,
collaborate, and communicate positively. The same platform can be extended to a fabricated …

CNN based on transfer learning models using data augmentation and transformation for detection of concrete crack

MM Islam, MB Hossain, MN Akhtar, MA Moni… - Algorithms, 2022 - mdpi.com
Cracks in concrete cause initial structural damage to civil infrastructures such as buildings,
bridges, and highways, which in turn causes further damage and is thus regarded as a …

Lung cancer detection from CT scans using modified DenseNet with feature selection methods and ML classifiers

MG Lanjewar, KG Panchbhai, P Charanarur - Expert Systems with …, 2023 - Elsevier
Lung cancer is a highly life-threatening disease worldwide, and detection is crucial. In this
study, the Kaggle chest CT-scan images dataset was used to identify lung cancer in four …

[HTML][HTML] DeepCrop: Deep learning-based crop disease prediction with web application

MM Islam, MAA Adil, MA Talukder… - Journal of Agriculture …, 2023 - Elsevier
Agriculture plays a significant role in every nation's economy by producing crops. Plant
disease identification is one of the most important aspects of maintaining an agriculturally …

A hybrid dependable deep feature extraction and ensemble-based machine learning approach for breast cancer detection

S Sharmin, T Ahammad, MA Talukder, P Ghose - IEEE Access, 2023 - ieeexplore.ieee.org
Breast cancer is a prevalent and life-threatening disease that requires effective detection
and diagnosis methods to improve patient outcomes. Deep learning (DL) and machine …