Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets
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 …
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …
Systematic review for lung cancer detection and lung nodule classification: Taxonomy, challenges, and recommendation future works
Nowadays, lung cancer is one of the most dangerous diseases that require early diagnosis.
Artificial intelligence has played an essential role in the medical field in general and in …
Artificial intelligence has played an essential role in the medical field in general and in …
FN-OCT: Disease detection algorithm for retinal optical coherence tomography based on a fusion network
Z Ai, X Huang, J Feng, H Wang, Y Tao… - Frontiers in …, 2022 - frontiersin.org
Optical coherence tomography (OCT) is a new type of tomography that has experienced
rapid development and potential in recent years. It is playing an increasingly important role …
rapid development and potential in recent years. It is playing an increasingly important role …
Cat swarm optimization-based computer-aided diagnosis model for lung cancer classification in computed tomography images
Lung cancer is the most significant cancer that heavily contributes to cancer-related mortality
rate, due to its violent nature and late diagnosis at advanced stages. Early identification of …
rate, due to its violent nature and late diagnosis at advanced stages. Early identification of …
A hybrid approach of vision transformers and CNNs for detection of ulcerative colitis
Abstract Ulcerative Colitis is an Inflammatory Bowel disease caused by a variety of factors
that lead to a serious impact on the quality of life of the patients if left untreated. Due to …
that lead to a serious impact on the quality of life of the patients if left untreated. Due to …
Pulmonary nodule classification using feature and ensemble learning-based fusion techniques
The Pulmonary nodule indicates the presence of lung cancer. The deep convolutional
neural networks (DCNNs) have been widely used to classify the pulmonary nodule as …
neural networks (DCNNs) have been widely used to classify the pulmonary nodule as …
An improved faster RCNN-based weld ultrasonic atlas defect detection method
C Chen, S Wang, S Huang - Measurement and control, 2023 - journals.sagepub.com
In view of the complex multi-scale target detection environment of ultrasonic atlas of weld
defect and the poor detection performance of existing algorithms for the multiple small target …
defect and the poor detection performance of existing algorithms for the multiple small target …
Multi-stage biomedical feature selection extraction algorithm for cancer detection
Cancer is a significant cause of death worldwide. Early cancer detection is greatly aided by
machine learning and artificial intelligence (AI) to gene microarray data sets (microarray …
machine learning and artificial intelligence (AI) to gene microarray data sets (microarray …
A proposed methodology for detecting the malignant potential of pulmonary nodules in sarcoma using computed tomographic imaging and artificial intelligence-based …
The presence of lung metastases in patients with primary malignancies is an important
criterion for treatment management and prognostication. Computed tomography (CT) of the …
criterion for treatment management and prognostication. Computed tomography (CT) of the …
Classification of lung nodules based on the DCA-Xception network
D Li, S Yuan, G Yao - Journal of X-ray Science and …, 2022 - content.iospress.com
BACKGROUND: Develo** deep learning networks to classify between benign and
malignant lung nodules usually requires many samples. Due to the precious nature of …
malignant lung nodules usually requires many samples. Due to the precious nature of …