Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Deep learning for lung cancer diagnosis, prognosis and prediction using histological and cytological images: a systematic review
Simple Summary Lung cancer is one of the most common and deadly malignancies
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
Histopathological Analysis for Detecting Lung and Colon Cancer Malignancies Using Hybrid Systems with Fused Features
Lung and colon cancer are among humanity's most common and deadly cancers. In 2020,
there were 4.19 million people diagnosed with lung and colon cancer, and more than 2.7 …
there were 4.19 million people diagnosed with lung and colon cancer, and more than 2.7 …
An End-to-End Lightweight Multi-Scale CNN for the Classification of Lung and Colon Cancer with XAI Integration
To effectively treat lung and colon cancer and save lives, early and accurate identification is
essential. Conventional diagnosis takes a long time and requires the manual expertise of …
essential. Conventional diagnosis takes a long time and requires the manual expertise of …
Medical Image Classifications Using Convolutional Neural Networks: A Survey of Current Methods and Statistical Modeling of the Literature
In this review, we compiled convolutional neural network (CNN) methods which have the
potential to automate the manual, costly and error-prone processing of medical images. We …
potential to automate the manual, costly and error-prone processing of medical images. We …
A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction
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 …
efficient and automated early detection methods. To address this critical need, this review …
An Advanced Lung Carcinoma Prediction and Risk Screening Model Using Transfer Learning
Lung cancer, also known as lung carcinoma, has a high death rate, but an early diagnosis
can substantially reduce this risk. In the current era, prediction models face challenges such …
can substantially reduce this risk. In the current era, prediction models face challenges such …
Al-Powered classification of Ovarian cancers Based on Histopathological lmages
H Kussaibi, E Alibrahim, E Alamer, G Alhaji… - medRxiv, 2024 - medrxiv.org
Background: Ovarian cancer is the leading cause of gynecological cancer deaths due to late
diagnosis and high recurrence rates. While histopathological analysis is the gold standard …
diagnosis and high recurrence rates. While histopathological analysis is the gold standard …
A Novel Attention-based Explainable Deep Learning Framework Towards Medical Image Classification
GW Muoka, D Yi, CC Ukwuoma… - … Approaches in Smart …, 2023 - ieeexplore.ieee.org
Deep learning applications for medical image classification have shown remarkable
promise, particularly incorporating attention-based neural networks. This is particularly …
promise, particularly incorporating attention-based neural networks. This is particularly …
Study & Analysis of Lung Cancer Risk Prediction Techniques Using ML and DL Algorithms
G Gupta, V Kumar… - 2024 IEEE Students …, 2024 - ieeexplore.ieee.org
Lung cancer remains a significant global health challenge as it causes most deaths around
the world, emphasizing the need for effective early detection and treatment strategies. The …
the world, emphasizing the need for effective early detection and treatment strategies. The …