Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
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 …
An enhanced approach for sentiment analysis based on meta-ensemble deep learning
R Kora, A Mohammed - Social Network Analysis and Mining, 2023 - Springer
Sentiment analysis, commonly known as “opinion mining,” aims to identify sentiment
polarities in opinion texts. Recent years have seen a significant increase in the acceptance …
polarities in opinion texts. Recent years have seen a significant increase in the acceptance …
Lung cancer diagnosis in CT images based on Alexnet optimized by modified Bowerbird optimization algorithm
Y Xu, Y Wang, N Razmjooy - Biomedical Signal Processing and Control, 2022 - Elsevier
Objective Cancer is the uncontrolled growth of abnormal cells that do not function as normal
cells. Lung cancer is the leading cause of cancer death in the world, so early detection of …
cells. Lung cancer is the leading cause of cancer death in the world, so early detection of …
RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics
Z Guo, L Xu, Y Si, N Razmjooy - International Journal of …, 2021 - Wiley Online Library
This study proposes a lung cancer diagnosis system based on computed tomography (CT)
scan images for the detection of the disease. The proposed method uses a sequential …
scan images for the detection of the disease. The proposed method uses a sequential …
A hybrid cancer prediction based on multi-omics data and reinforcement learning state action reward state action (SARSA)
These days, the ratio of cancer diseases among patients has been growing day by day.
Recently, many cancer cases have been reported in different clinical hospitals. Many …
Recently, many cancer cases have been reported in different clinical hospitals. Many …
Federated auto-encoder and XGBoost schemes for multi-omics cancer detection in distributed fog computing paradigm
The digital healthcare paradigm has significantly improved based on distributed fog and
cloud networks for cancer detection with multiple classes in recent years. The paradigm …
cloud networks for cancer detection with multiple classes in recent years. The paradigm …
Improving pneumonia detection in chest X-rays using transfer learning approach (AlexNet) and adversarial training
The method outlined in this paper employs transfer learning and adversarial training to
enhance the precision of pneumonia identification in chest X-rays. The authors use the …
enhance the precision of pneumonia identification in chest X-rays. The authors use the …
Classification of non-small cell lung cancer using one-dimensional convolutional neural network
Abstract Non-Small Cell Lung Cancer (NSCLC) is a major lung cancer type. Proper
diagnosis depends mainly on tumor staging and grading. Pathological prognosis often faces …
diagnosis depends mainly on tumor staging and grading. Pathological prognosis often faces …
A survey of computer-aided tumor diagnosis based on convolutional neural network
Simple Summary One of the hottest areas in deep learning is computerized tumor diagnosis
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …