INTRODUCTION: Machine learning is applied to characterize the risk and predict outcomes in multi-dimensional data. The prediction of radiographic progression in axial spondyloarthritis (axSpA) remains limited. Hence, we tested the feasibility of supe...
Journal of adolescent and young adult oncology
Oct 30, 2019
Treatment of pediatric cancers and hematological malignancies requires long periods of isolation in a sterile room. To promote family connections, telepresence robots have been made available in the homes of hospitalized patients. Our aim was to eva...
Systematic, structured and longitudinal collection of realtime Big Patient Data and the analysis of aggregated diagnostic, therapeutic and therapy response data of onco-hematologic patients leads to the development of nationwide dynamic disease regis...
The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-based approach for fall detection and classification...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 30, 2019
Assistive robotic arms have become popular to help users with upper limb disabilities achieve autonomy in their daily tasks, such as drinking and grasping objects in general. Usually, these robotic arms are controlled with an adapted joystick. Joysti...
Deep learning algorithms have achieved great success in cancer image classification. However, it is imperative to understand the differences between the deep learning and human approaches. Using an explainable model, we aimed to compare the deep lear...
Seeking smaller and indistinct incisions, physicians have attempted endoscopic breast surgery in breast cancer patients. Unfortunately, there are some limitations in the range of movement and visualization of the operation field. Potentially addressi...
Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from...
The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pa...
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