Latest AI and machine learning research in medical education for healthcare professionals.
Robot learning requires a considerable amount of high-quality data to realize the promise of gener...
In this work, we present INTACT, a novel two-phase framework designed to enhance the robustness of...
Model order reduction (MOR) involves offering low-dimensional models that effectively approximate ...
The advancement of large language models (LLMs) has opened new frontiers in natural language proce...
Current medical AI systems often fail to replicate real-world clinical reasoning, as they are pred...
While learning personalization offers great potential for learners, modern practices in higher edu...
Automotive Simulation is a potentially cost-effective strategy to identify and test corner case sc...
Long-form egocentric video understanding provides rich contextual information and unique insights ...
Accurate medical image segmentation is often hindered by noisy labels in training data, due to the...
Medical imaging is crucial for diagnosing, monitoring, and treating medical conditions. The medica...
A high-fidelity digital simulation environment is crucial for accurately replicating physical oper...
Recent advances in large language models (LLMs) have accelerated the development of conversational...
The application of machine learning to the study of coronal mass ejections (CMEs) and their impact...
Systems neuroscience has experienced an explosion of new tools for reading and writing neural activi...
Center-port fixation is a common prerequisite for many freely-moving rodent tasks in neuroscience an...
Biophysical simulations have guided the development of blood oxygenation level-dependent (BOLD) func...
Here we are introducing CryoPhold, a modular workflow that unifies AlphaFold-based ensemble generati...
VCFs are the most widely used data format for encoding genetic variation. By design, standard VCFs d...
The GluN1/GluN2A N-methyl-D-aspartate receptor (NMDAR) is a critical ligand-gated ion channel in the...
Detecting mass extinction events from phylogenies is a fundamental yet challenging task. While tradi...
Deep generative models for protein structure and sequence are increasingly used to design proteins w...