AI Medical Compendium Topic

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Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme.

Computational intelligence and neuroscience
PURPOSE: The need for computerized medical assistance for accurate detection of brain hemorrhage from Computer Tomography (CT) images is more mandatory than conventional clinical tests. Recent technologies and advanced computerized algorithms follow ...

Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have contributed to a desire for novel technologies and paradigms, includi...

Multilevel Structural Components Detection and Segmentation toward Computer Vision-Based Bridge Inspection.

Sensors (Basel, Switzerland)
Bridge inspection plays a critical role in mitigating the safety risks associated with bridge deterioration and decay. CV (computer vision) technology can facilitate bridge inspection by accurately automating the structural recognition tasks, especia...

Multi-state MRAM cells for hardware neuromorphic computing.

Scientific reports
Magnetic tunnel junctions (MTJ) have been successfully applied in various sensing application and digital information storage technologies. Currently, a number of new potential applications of MTJs are being actively studied, including high-frequency...

Adaptive Contrast for Image Regression in Computer-Aided Disease Assessment.

IEEE transactions on medical imaging
Image regression tasks for medical applications, such as bone mineral density (BMD) estimation and left-ventricular ejection fraction (LVEF) prediction, play an important role in computer-aided disease assessment. Most deep regression methods train t...

An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems.

IEEE transactions on neural networks and learning systems
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such ...

Computer Vision-Based Medical Cloud Data System for Back Muscle Image Detection.

Computational intelligence and neuroscience
The fast development of image recognition and information technology has influenced people's life and industry management mode not only in some common fields such as information management, but also has very much improved the working efficiency of va...

Deep Learning for Ocular Disease Recognition: An Inner-Class Balance.

Computational intelligence and neuroscience
It can be challenging for doctors to identify eye disorders early enough using fundus pictures. Diagnosing ocular illnesses by hand is time-consuming, error-prone, and complicated. Therefore, an automated ocular disease detection system with computer...

Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review.

Sensors (Basel, Switzerland)
Road condition monitoring (RCM) has been a demanding strategic research area in maintaining a large network of transport infrastructures. With advancements in computer vision and data mining techniques along with high computing resources, several inn...