Results 61 to 70 of about 1,540,853 (195)
Abstract Introduction Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a misalignment between AI systems and their users.
Luca M. Heising+11 more
wiley +1 more source
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class ...
Chen, Huajun+6 more
core
Abstract Purpose This work introduces BreastWatch, a Varian Eclipse script tool designed to help medical physicists, dosimetrists, and radiation oncologists easily inspect and improve External Beam Breast Treatment (EBBT) plans using automatic evaluation of protocol dose‐constraints enhanced by a Community‐Based approach.
Stefano Agostinelli+8 more
wiley +1 more source
Abstract Purpose In radiation oncology, the integration and registration of multiple imaging modalities is a crucial aspect of the diagnosis and treatment planning process. These images are often inherently registered, a useful feature in most cases, but possibly a hindrance when registration modifications are required.
Brian M. Anderson, Casey Bojechko
wiley +1 more source
Histone Deacetylase 6 Brain PET in Amyotrophic Lateral Sclerosis‐Frontotemporal Spectrum Disorder
ABSTRACT Objective [18F]EKZ‐001 is a positron emission tomography (PET) tracer targeting histone deacetylase 6 (HDAC6), an enzyme responsible for intracellular transport and clearance of misfolded proteins. HDAC6 modulation is a promising treatment strategy in neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS).
Greet Vanderlinden+15 more
wiley +1 more source
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi+4 more
wiley +1 more source
Objective This study analyzed longitudinal trajectories of soluble Flt1 (sFlt1) levels, placenta growth factor (PlGF) levels, and sFlt1:PlGF ratios in a cohort of pregnant patients with systemic lupus erythematosus (SLE). Methods Blood samples were collected (14–18, 24–26, 30–32, 34–36, and 38–40 weeks), stored at −80°C, and evaluated for serum levels ...
Nilson R. de Jesús+7 more
wiley +1 more source
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning [PDF]
Autoregressive large language models (LLMs) pre-trained by next token prediction are inherently proficient in generative tasks. However, their performance on knowledge-driven tasks such as factual knowledge querying remains unsatisfactory. Knowledge graphs (KGs), as high-quality structured knowledge bases, can provide reliable knowledge for LLMs ...
arxiv
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez+2 more
wiley +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani+2 more
wiley +1 more source