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Found 3 papers, 1 papers with code
Development of RLK-Unet: a clinically favorable deep learning algorithm for brain metastasis detection and treatment response assessment
Methods and materials: A total of 128 patients with 1339 BMs, who underwent BM magnetic resonance imaging using the contrast-enhanced 3D T1 weighted (T1WI) turbo spin-echo black blood sequence, were included in the development of the DL algorithm.
Gait-based Human Identification through Minimum Gait-phases and Sensors
It was shown that it is possible to achieve high accuracy of over 95. 5 percent by monitoring a single phase of the whole gait cycle through only a single sensor.
Gait-based Frailty Assessment using Image Representation of IMU Signals and Deep CNN
In this paper, it is shown that by encoding gait signals as images, deep learning-based models can be utilized for the classification of gait type.
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