Latest AI and machine learning research in work force for healthcare professionals.
Humanoid loco-manipulation holds transformative potential for daily service and industrial tasks, yet achieving precise, robust whole-body control with 3D end-effector force interaction remains a major challenge. Prior approaches are often limited to lightweight tasks or quadrupedal/wheeled platforms. To overcome these limitations, we propose FALCON, a dual-agent reinforcement-learning-based fra...
Global patterns of intraspecific genetic diversity are key to understanding evolutionary and ecological processes. However, insights into the distribution and drivers of genetic diversity remain limited, particularly for marine species. Here, we explain and predict the genetic diversity of cold and temperate brown macroalgae using genetic data from 29 species and a machine-learning algorithm that ...
Accurate defect detection of photovoltaic (PV) cells is critical for ensuring quality and efficiency in intelligent PV manufacturing systems. Howeve...
: In 2010, approximately 60.5 million people were affected by glaucoma, making it the leading cause of permanent vision impairment globally. With the ...
3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as imme...
Generating a synthetic population that is both feasible and diverse is crucial for ensuring the validity of downstream activity schedule simulation ...
Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to const...
Recent advances in personalized MLLMs enable effective capture of user-specific concepts, supporting both recognition of personalized concepts and c...
While modern Requirements Engineering (RE) heavily relies on natural language processing and Machine Learning (ML) techniques, their effectiveness i...
MOTIVATION: Molecular property prediction with deep learning has accelerated drug discovery and retrosynthesis. However, the shortage of labeled molec...
Visual prompting techniques are widely used to efficiently fine-tune pretrained Vision Transformers (ViT) by learning a small set of shared prompts ...
Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t...
Large Language Models (LLMs) have brought about revolutionary changes in diverse fields, rendering LLM training of utmost importance for modern ente...
PURPOSE: This study reports the implementation of a proof-of-concept, artificial intelligence (AI)-driven clinical decision support system for detecti...
Identification of T cell receptor (TCR) specificities for antigens from large-scale single-cell or bulk TCR repertoire data plays a vital role in dise...
Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, the integration of AI into nuclear medi...
Generative artificial intelligence, including large language models (LLMs), holds immense potential to enhance healthcare, medical education, and heal...
BACKGROUND: Nurses face an escalating workload, including tasks not directly related to patient care, such as responding to patients' requests for wat...
Image deocclusion (or amodal completion) aims to recover the invisible regions (\ie, shape and appearance) of occluded instances in images. Despite ...
Patients with neurological conditions require rehabilitation to restore their motor, visual, and cognitive abilities. To meet the shortage of therap...