Applications and techniques of machine learning in cancer classification: A systematic review

A Yaqoob, R Musheer Aziz, NK verma - Human-Centric Intelligent Systems, 2023 - Springer
The domain of Machine learning has experienced Substantial advancement and
development. Recently, showcasing a Broad spectrum of uses like Computational …

Feature-enhanced deep learning technique with soft attention for MRI-based brain tumor classification

BC Mohanty, PK Subudhi, R Dash… - International Journal of …, 2024 - Springer
Brain tumor classification using Magnetic Resonance Imaging (MRI) is a pivotal area in
medical diagnostics, with the potential to influence early detection and subsequent treatment …

A systematic literature analysis of multi-organ cancer diagnosis using deep learning techniques

J Kaur, P Kaur - Computers in Biology and Medicine, 2024 - Elsevier
Cancer is becoming the most toxic ailment identified among individuals worldwide. The
mortality rate has been increasing rapidly every year, which causes progression in the …

Hybrid‐NET: A fusion of DenseNet169 and advanced machine learning classifiers for enhanced brain tumor diagnosis

SUR Khan, M Zhao, S Asif… - International Journal of …, 2024 - Wiley Online Library
The computer‐aided diagnostic (CAD) method to detect human brain tumors relies heavily
on automated tumor characterization. Although CAD method has been extensively …

Multi-class classification of brain tumour magnetic resonance images using multi-branch network with inception block and five-fold cross validation deep learning …

D Rastogi, P Johri, V Tiwari, AA Elngar - Biomedical Signal Processing and …, 2024 - Elsevier
The expertise of radiologists plays a pivotal role in the intricate task of diagnosing brain
tumors. However, the escalating number of patients has rendered traditional diagnostic …

Segmentation and classification of medical big data on brain tumor using bacteria foraging optimization algorithm along with learning automata

DS Keerthi, C Maithri, M Dayanidhi… - Internet Technology …, 2023 - Wiley Online Library
Detecting the early stage of brain tumors is significant for an effective therapy that can
probably minimize the death rate of patients affected from brain tumors. Magnetic resonance …

In-domain transfer learning strategy for tumor detection on brain MRI

DS Terzi, N Azginoglu - Diagnostics, 2023 - mdpi.com
Transfer learning has gained importance in areas where there is a labeled data shortage.
However, it is still controversial as to what extent natural image datasets as pre-training …

[HTML][HTML] Empowering Brain Tumor Diagnosis through Explainable Deep Learning

Z Li, O Dib - Machine Learning and Knowledge Extraction, 2024 - mdpi.com
Brain tumors are among the most lethal diseases, and early detection is crucial for improving
patient outcomes. Currently, magnetic resonance imaging (MRI) is the most effective method …

Optimized brain tumor identification via graph sample and aggregate-attention network with Artificial Lizard Search Algorithm

C Moorthy, JC Sekhar, SI Khan, G Agrawal - Knowledge-Based Systems, 2024 - Elsevier
A brain tumour is an abnormal growth of brain nerves that interferes with normal brain
function. It causes a great deal of deaths. Timely detection and treatment are essential for …

ChatGPT-powered deep learning: elevating brain tumor detection in MRI scans

S Rawas, C Tafran, D AlSaeed - Applied Computing and Informatics, 2024 - emerald.com
Purpose Accurate diagnosis of brain tumors is crucial for effective treatment and improved
patient outcomes. Magnetic resonance imaging (MRI) is a common method for detecting …