AI Medical Compendium Topic

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Computer Systems

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Global and Local Knowledge-Aware Attention Network for Action Recognition.

IEEE transactions on neural networks and learning systems
Convolutional neural networks (CNNs) have shown an effective way to learn spatiotemporal representation for action recognition in videos. However, most traditional action recognition algorithms do not employ the attention mechanism to focus on essent...

Deep-Learning Image Reconstruction for Real-Time Photoacoustic System.

IEEE transactions on medical imaging
Recent advances in photoacoustic (PA) imaging have enabled detailed images of microvascular structure and quantitative measurement of blood oxygenation or perfusion. Standard reconstruction methods for PA imaging are based on solving an inverse probl...

Real-time automatic surgical phase recognition in laparoscopic sigmoidectomy using the convolutional neural network-based deep learning approach.

Surgical endoscopy
BACKGROUND: Automatic surgical workflow recognition is a key component for developing the context-aware computer-assisted surgery (CA-CAS) systems. However, automatic surgical phase recognition focused on colorectal surgery has not been reported. We ...

Artificial immune intelligence-inspired dynamic real-time computer forensics model.

Mathematical biosciences and engineering : MBE
Dynamic computer forensics is a popular area in computer forensics that combines network intrusion technology with computer forensics technology. A novel dynamic computer forensics model is proposed based on an artificial immune system. Simulating th...

α-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States.

IEEE journal of biomedical and health informatics
The fast evolving and deadly outbreak of coronavirus disease (COVID-19) has posed grand challenges to human society. To slow the spread of virus infections and better respond for community mitigation, by advancing capabilities of artificial intellige...

Performance improvement of mediastinal lymph node severity detection using GAN and Inception network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In lung cancer, the determination of mediastinal lymph node (MLN) status as benign or malignant influence treatment planning and survival rate. Invasive pathological tests for the classification of MLNs into benign and malig...

Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

European radiology
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and c...

Deep Learning-Based Real-Time Multiple-Person Action Recognition System.

Sensors (Basel, Switzerland)
Action recognition has gained great attention in automatic video analysis, greatly reducing the cost of human resources for smart surveillance. Most methods, however, focus on the detection of only one action event for a single person in a well-segme...

Agents and robots for collaborating and supporting physicians in healthcare scenarios.

Journal of biomedical informatics
Monitoring patients through robotics telehealth systems is an interesting scenario where patients' conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems' features to include the ability to serv...

Development of a real-time indoor location system using bluetooth low energy technology and deep learning to facilitate clinical applications.

Medical physics
PURPOSE: An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy because Bl...