[HTML][HTML] Deep learning techniques to diagnose lung cancer
L Wang - Cancers, 2022 - mdpi.com
Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …
research directions of deep learning techniques for lung cancer and pulmonary nodule …
[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
[HTML][HTML] Thyroid nodule classification in ultrasound images by fine-tuning deep convolutional neural network
With many thyroid nodules being incidentally detected, it is important to identify as many
malignant nodules as possible while excluding those that are highly likely to be benign from …
malignant nodules as possible while excluding those that are highly likely to be benign from …
Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks
Accurate diagnosis of thyroid nodules using ultrasonography is a valuable but tough task
even for experienced radiologists, considering both benign and malignant nodules have …
even for experienced radiologists, considering both benign and malignant nodules have …
A pre-trained convolutional neural network based method for thyroid nodule diagnosis
In ultrasound images, most thyroid nodules are in heterogeneous appearances with various
internal components and also have vague boundaries, so it is difficult for physicians to …
internal components and also have vague boundaries, so it is difficult for physicians to …
Ultrasound-based differentiation of malignant and benign thyroid Nodules: An extreme learning machine approach
Background and objectives It is important to be able to accurately distinguish between
benign and malignant thyroid nodules in order to make appropriate clinical decisions. The …
benign and malignant thyroid nodules in order to make appropriate clinical decisions. The …
SVM‐RFE based feature selection and Taguchi parameters optimization for multiclass SVM classifier
ML Huang, YH Hung, WM Lee, RK Li… - The Scientific World …, 2014 - Wiley Online Library
Recently, support vector machine (SVM) has excellent performance on classification and
prediction and is widely used on disease diagnosis or medical assistance. However, SVM …
prediction and is widely used on disease diagnosis or medical assistance. However, SVM …
[HTML][HTML] Ultrasound image-based diagnosis of malignant thyroid nodule using artificial intelligence
Computer-aided diagnosis systems have been developed to assist doctors in diagnosing
thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly …
thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly …
Pulmonary nodule classification with deep convolutional neural networks on computed tomography images
Computer aided detection (CAD) systems can assist radiologists by offering a second
opinion on early diagnosis of lung cancer. Classification and feature representation play …
opinion on early diagnosis of lung cancer. Classification and feature representation play …
Multitask cascade convolution neural networks for automatic thyroid nodule detection and recognition
Thyroid ultrasonography is a widely used clinical technique for nodule diagnosis in thyroid
regions. However, it remains difficult to detect and recognize the nodules due to low …
regions. However, it remains difficult to detect and recognize the nodules due to low …