AIMC Topic: Deep Learning

Clear Filters Showing 21911 to 21920 of 28423 articles

Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Radiology
Although computer-aided diagnosis (CAD) is widely used in mammography, conventional CAD programs that use prompts to indicate potential cancers on the mammograms have not led to an improvement in diagnostic accuracy. Because of the advances in machin...

Machine Learning-Enabled Automated Determination of Acute Ischemic Core From Computed Tomography Angiography.

Stroke
Background and Purpose- The availability of and expertise to interpret advanced neuroimaging recommended in the guideline-based endovascular stroke therapy (EST) evaluation are limited. Here, we develop and validate an automated machine learning-base...

A Survey of Vision-Based Human Action Evaluation Methods.

Sensors (Basel, Switzerland)
The fields of human activity analysis have recently begun to diversify. Many researchers have taken much interest in developing action recognition or action prediction methods. The research on human action evaluation differs by aiming to design compu...

Sequential Saliency Guided Deep Neural Network for Joint Mitosis Identification and Localization in Time-Lapse Phase Contrast Microscopy Images.

IEEE journal of biomedical and health informatics
The analysis of cell mitotic behavior plays important role in many biomedical research and medical diagnostic applications. To improve the accuracy of mitosis detection in automated analysis systems, this paper proposes the sequential saliency guided...

Inter-Patient ECG Classification With Symbolic Representations and Multi-Perspective Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
This paper presents a novel deep learning framework for the inter-patient electrocardiogram (ECG) heartbeat classification. A symbolization approach especially designed for ECG is introduced, which can jointly represent the morphology and rhythm of t...

Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification.

IEEE journal of biomedical and health informatics
Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. However, recent researches show that a well-trained deep learning model may not generalize well to data from different cohorts due to domain shift. Sim...

Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears.

IEEE journal of biomedical and health informatics
OBJECTIVE: This work investigates the possibility of automated malaria parasite detection in thick blood smears with smartphones.

Operation-aware Neural Networks for user response prediction.

Neural networks : the official journal of the International Neural Network Society
User response prediction makes a crucial contribution to the rapid development of online advertising system and recommendation system. The importance of learning feature interactions has been emphasized by many works. Many deep models are proposed to...

Automated Assessment of Oral Diadochokinesis in Multiple Sclerosis Using a Neural Network Approach: Effect of Different Syllable Repetition Paradigms.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Slow and irregular oral diadochokinesis represents an important manifestation of spastic and ataxic dysarthria in multiple sclerosis (MS). We aimed to develop a robust algorithm based on convolutional neural networks for the accurate detection of syl...