AIMC Topic: Models, Theoretical

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Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling to Machine Learning.

Ultrasound in medicine & biology
Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell....

Real-time prediction of tumor motion using a dynamic neural network.

Medical & biological engineering & computing
Radiation dose delivery into the thoracic and abdomen cavities during radiotherapy treatment is a challenging task as respiratory motion leads to the motion of the target tumor. Real-time repositioning of the treatment beam during radiotherapy requir...

Fluidic Fabric Muscle Sheets for Wearable and Soft Robotics.

Soft robotics
Conformable robotic systems are attractive for applications in which they may actuate structures with large surface areas, provide forces through wearable garments, or enable autonomous robotic systems. We present a new family of soft actuators that ...

Risk perception and behavioral change during epidemics: Comparing models of individual and collective learning.

PloS one
Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research age...

Learning efficient haptic shape exploration with a rigid tactile sensor array.

PloS one
Haptic exploration is a key skill for both robots and humans to discriminate and handle unknown objects or to recognize familiar objects. Its active nature is evident in humans who from early on reliably acquire sophisticated sensory-motor capabiliti...

Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.

Medical physics
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...

A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition)
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...

Control of speaking rate is achieved by switching between qualitatively distinct cognitive "gaits": Evidence from simulation.

Psychological review
That speakers can vary their speaking rate is evident, but how they accomplish this has hardly been studied. Consider this analogy: When walking, speed can be continuously increased, within limits, but to speed up further, humans must run. Are there ...

Neural Network Ensembles for Sensor-Based Human Activity Recognition Within Smart Environments.

Sensors (Basel, Switzerland)
In this paper, we focus on data-driven approaches to human activity recognition (HAR). Data-driven approaches rely on good quality data during training, however, a shortage of high quality, large-scale, and accurately annotated HAR datasets exists fo...