Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...
Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wavelength precision in microvasculature imaging by tracking gas microbubbles (MBs) flowing through bloo...
Gastric Tract Disease (GTD) constitutes a medical emergency, emphasizing the critical importance of early diagnosis and intervention to lessen its severity. Clinical practices often utilize endoscopy-supported examinations for GTD screening. The imag...
BACKGROUND: Understanding and improving patient care is pivotal for health care providers. With increasing volumes of the Friends and Family Test (FFT) data in England, manual analysis of this patient feedback poses challenges for many health care or...
Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinical decisions and improving patient outcomes. This study addresses the challenges of imbalanced data in SAH severity classification by employing the Mo...
Current virtual imaging phantoms primarily emphasize geometric accuracy of anatomical structures. However, to enhance realism, it is also important to incorporate intra-organ detail. Because biological tissues are heterogeneous in composition, virtua...
. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses. Prevailing research into classifying electromyographic (EMG) muscular data or electroencephalographic (EEG) brain data for this purpose is often lim...
Spiking neural networks (SNNs) are emerging as a promising evolution in neural network paradigms, offering an alternative to conventional convolutional neural networks (CNNs). One of the most effective methods for SNN development is the CNN-to-SNN co...
Accurate nuclei segmentation and classification in histology images are critical for cancer detection but remain challenging due to color inconsistency, blurry boundaries, and overlapping nuclei. Manual segmentation is time-consuming and labor-intens...
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