The integration of deep learning in medical imaging has significantly advanced diagnostic, therapeutic, and research outcomes. However, applying universal models across multiple modalities remains challenging due to inherent inter-modality variabilit...
Self-supervised denoising methods significantly enhance the signal-to-noise ratio in fluorescence neural imaging, yet real-time solutions remain scarce in high-speed applications. Here, we present the FrAme-multiplexed SpatioTemporal learning strateg...
Deep learning models are prone to failure when inferring upon out-of-distribution (OOD) data, i.e. data whose features fundamentally differ from those in the training set. Existing OOD measures often lack sensitivity to the subtle image variations en...
A brain tumor is one of the life-threatening neurological conditions affecting millions of people worldwide. Early diagnosis and classification of brain tumor types facilitate prompt treatment, thereby increasing the patient's chances of survival. Th...
The advancement in computing technology, online learning platforms, and pedagogical tools enable educators and learners to connect without temporal and geographical boundaries. The existing deep learning models to predict student performance are eith...
This paper examines the escalating challenge of detecting cyber-attacks within Internet of Things (IoT) networks, where conventional security measures often falter in addressing the speed and complexity of contemporary threats. In response to the nec...
PURPOSE: To propose a multi-parametric ultrasound imaging-based deep learning method for accurately classifying metastatic and non-metastatic axillary lymph nodes in breast cancer patients.
BACKGROUND: Strabismus is a common ocular misalignment that can impair binocular vision if untreated. Conventional diagnosis and treatment rely on clinical prism diopter (PD) readings, which quantify deviation along with base direction. However, thes...
Sepsis is a life-threatening condition resulting from a dysregulated immune response to infection, often leading to organ failure and death. Early detection is vital, as delays significantly worsen outcomes. In recent years, the integration of artifi...
Kidney stone disease is a common syndrome and a recurring one, where it bears a 50% chance of being manifested again within ten years and may lead to serious complications like ureteral obstruction and unbearable pain. If timely intervention is consi...
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