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 …

[HTML][HTML] Detection of various gastrointestinal tract diseases through a deep learning method with ensemble ELM and explainable AI

MF Ahamed, M Nahiduzzaman, MR Islam… - Expert Systems with …, 2024 - Elsevier
The rising prevalence of gastrointestinal (GI) tract disorders worldwide highlights the urgent
need for precise diagnosis, as these diseases greatly affect human life and contribute to …

GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images

MN Noor, M Nazir, I Ashraf, NA Almujally… - CAAI Transactions …, 2023 - Wiley Online Library
Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and
have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare …

[HTML][HTML] 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 …

[HTML][HTML] Gastrovrg: Enhancing early screening in gastrointestinal health via advanced transfer features

MS Islam, MAT Rony, T Sultan - Intelligent Systems with Applications, 2024 - Elsevier
The accurate classification of endoscopic images is a challenging yet critical task in medical
diagnostics, which directly affects the treatment and management of Gastrointestinal …

[HTML][HTML] Localization and classification of gastrointestinal tract disorders using explainable AI from endoscopic images

M Nouman Noor, M Nazir, SA Khan, I Ashraf… - Applied Sciences, 2023 - mdpi.com
Globally, gastrointestinal (GI) tract diseases are on the rise. If left untreated, people may die
from these diseases. Early discovery and categorization of these diseases can reduce the …

Multi-classification deep learning models for detection of ulcerative colitis, polyps, and dyed-lifted polyps using wireless capsule endoscopy images

H Malik, A Naeem, A Sadeghi-Niaraki… - Complex & Intelligent …, 2024 - Springer
Wireless capsule endoscopy (WCE) enables imaging and diagnostics of the gastrointestinal
(GI) tract to be performed without any discomfort. Despite this, several characteristics …

A convolutional neural network with meta-feature learning for wireless capsule endoscopy image classification

S Jain, A Seal, A Ojha - Journal of Medical and Biological Engineering, 2023 - Springer
Abstract Purpose Wireless Capsule Endoscopy is a widely used method for gastrointestinal
tract inspection. Automatic gastrointestinal abnormality detection systems face a key issue of …

Explainable AI for gastrointestinal disease diagnosis in telesurgery Healthcare 4.0

M Patel, K Gohil, A Gohil, F Ramoliya, R Gupta… - Computers and …, 2024 - Elsevier
The escalating prevalence of gastrointestinal disorders, spanning a spectrum from polyps to
tumors, underscores the imperative for advanced diagnostic and interventional …

[HTML][HTML] Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images

VY Cambay, PD Barua, A Hafeez Baig, S Dogan… - Sensors, 2024 - mdpi.com
This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to
detect various gastrointestinal diseases using a new ResNet50*-based deep feature …