Latest AI and machine learning research in medical education for healthcare professionals.
De novo molecular design has extensive applications in drug discovery and materials science. The vast chemical space renders direct molecular searches computationally prohibitive, while traditional experimental screening is both time- and labor-intensive. Efficient molecular generation and screening methods are therefore essential for accelerating drug discovery and reducing costs. Although rein...
Large language models (LLMs) have the potential to transform medicine, but real-world clinical scenarios contain extraneous information that can hinder performance. The rise of assistive technologies like ambient dictation, which automatically generates draft notes from live patient encounters, has the potential to introduce additional noise making it crucial to assess the ability of LLM's to fi...
This paper presents a novel approach for accelerating n-body simulations by integrating a physics-informed graph neural networks (GNN) with traditio...
Recent advancements in image and video synthesis have opened up new promise in generative games. One particularly intriguing application is transfor...
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement an...
Artificial intelligence (AI) is redefining medical education, bringing new dimensions of personalized learning, enhanced visualization and simulation-...
BACKGROUND: Applications of artificial intelligence (AI) in medicine are expanding every year. AI education is crucial to its appropriate use in healt...
BACKGROUND: Large language models (LLMs) have revolutionized the way physicians access and leverage artificial intelligence (AI). The potential role o...
In orthodontic treatment, the biological response of the tooth, periodontal ligament, and bone complex to orthodontic force is crucial in influencin...
Artificial Intelligence (AI) has been advancing rapidly and with the advent of large language models (LLMs) in late 2022, numerous opportunities hav...
We introduce Scenario Dreamer, a fully data-driven generative simulator for autonomous vehicle planning that generates both the initial traffic scen...
The advent of edge intelligence and escalating concerns for data privacy protection have sparked a surge of interest in device-cloud collaborative c...
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and ...
As green, sustainable, and environmentally friendly material processing processes using biological cells or enzymes to achieve substance conversion, b...
Dataset distillation (DD) excels in synthesizing a small number of images per class (IPC) but struggles to maintain its effectiveness in high-IPC se...
This work concerns itself with the task of reconstructing all edges of an arbitrary 3D wire-frame model projected to an image plane. We explore a bo...
Image restoration is essential for enhancing degraded images across computer vision tasks. However, most existing methods address only a single type...
We present Shap-MeD, a text-to-3D object generative model specialized in the biomedical domain. The objective of this study is to develop an assista...
Observing and forecasting coronal mass ejections (CME) in real-time is crucial due to the strong geomagnetic storms they can generate that can have ...
Recent video diffusion models have enhanced video editing, but it remains challenging to handle instructional editing and diverse tasks (e.g., addin...