Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment

C Zhang, J Xu, R Tang, J Yang, W Wang, X Yu… - Journal of Hematology & …, 2023 - Springer
Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic …

HM Rai, J Yoo, A Razaque - Expert Systems with Applications, 2024 - Elsevier
Cancer remains a leading reason of mortality, with the current global death toll estimated at
10 million and projected to surpass 16 million by 2040 as reported by the World Health …

An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images

M Khalid, S Deivasigamani, SV, S Rajendran - Scientific Reports, 2024 - nature.com
The second most common type of malignant tumor worldwide is colorectal cancer.
Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal …

Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets

HM Rai, J Yoo, SA Moqurrab, S Dashkevych - Measurement, 2024 - Elsevier
Accurate cancer detection and diagnosis are imperative for advancing patient outcomes and
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …

Color-CADx: a deep learning approach for colorectal cancer classification through triple convolutional neural networks and discrete cosine transform

M Sharkas, O Attallah - Scientific Reports, 2024 - nature.com
Colorectal cancer (CRC) exhibits a significant death rate that consistently impacts human
lives worldwide. Histopathological examination is the standard method for CRC diagnosis …

A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction

HM Rai, J Yoo, A Razaque - Medical & Biological Engineering & …, 2024 - Springer
The fight against cancer, a relentless global health crisis, emphasizes the urgency for
efficient and automated early detection methods. To address this critical need, this review …

CViTS-Net: A CNN-ViT Network with Skip Connections for Histopathology Image Classification

A Kanadath, JAA Jothi, S Urolagin - IEEE Access, 2024 - ieeexplore.ieee.org
Histopathological image classification stands as a cornerstone in the pathological diagnosis
workflow, yet it remains challenging due to the inherent complexity of histopathological …

EL-CNN: An enhanced lightweight classification method for colorectal cancer histopathological images

XL Pan, B Hua, K Tong, X Li, JL Luo, H Yang… - … Signal Processing and …, 2025 - Elsevier
Colorectal cancer (CRC) histopathological image classification is a critical part of
diagnosing CRC. In this context, the classification efficiency of deep learning methods is …

An improved multi-scale gradient generative adversarial network for enhancing classification of colorectal cancer histological images

L Jiang, S Huang, C Luo, J Zhang, W Chen… - Frontiers in …, 2023 - frontiersin.org
Introduction Deep learning-based solutions for histological image classification have gained
attention in recent years due to their potential for objective evaluation of histological images …

Analysis of Colorectal and Gastric Cancer Classification: A Mathematical Insight Utilizing Traditional Machine Learning Classifiers

HM Rai, J Yoo - Mathematics, 2023 - mdpi.com
Cancer remains a formidable global health challenge, claiming millions of lives annually.
Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored …