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Human activity recognition in artificial intelligence framework: a narrative review
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: A narrative review for stroke application
Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the
United States of America and globally. Carotid arterial plaque, a cause and also a marker of …
United States of America and globally. Carotid arterial plaque, a cause and also a marker of …
Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
Motivation Brain or central nervous system cancer is the tenth leading cause of death in men
and women. Even though brain tumour is not considered as the primary cause of mortality …
and women. Even though brain tumour is not considered as the primary cause of mortality …
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 …
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 …
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 …
Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks
Thyroid cancer is a disease in which the first symptom is a nodule in the thyroid region of the
neck. It is one of the cancers with the highest incidences, and has the highest increase rate …
neck. It is one of the cancers with the highest incidences, and has the highest increase rate …
Deep learning-based CAD system design for thyroid tumor characterization using ultrasound images
Abstract Computer-Aided Diagnosis (CAD) system is preferred for automatic thyroid tumor
ultrasound image characterization instead of manual assessment by the experts …
ultrasound image characterization instead of manual assessment by the experts …
Multi-channel convolutional neural network architectures for thyroid cancer detection
Early detection of malignant thyroid nodules leading to patient-specific treatments can
reduce morbidity and mortality rates. Currently, thyroid specialists use medical images to …
reduce morbidity and mortality rates. Currently, thyroid specialists use medical images to …