Artificial intelligence in four-dimensional imaging for motion management in radiation therapy [0.03%]
人工智能在放射治疗运动管理的四维成像中的应用
Wang Yinghui,Xiao Haonan,Wang Jing et al.
Wang Yinghui et al.
Four-dimensional imaging (4D-imaging) plays a critical role in achieving precise motion management in radiation therapy. However, challenges remain in 4D-imaging such as a long imaging time, suboptimal image quality, and inaccurate motion e...
Applications of machine learning for computer-aided diagnosis of Parkinson's disease: progress and benchmark case study [0.03%]
机器学习在计算机辅助诊断帕金森病中的应用：进展与基准案例研究
Juntao Zhang,Yiming Zhang,Ying Weng et al.
Juntao Zhang et al.
Machine learning (ML) has emerged as a vital tool for the diagnosis of Parkinson's Disease (PD). This study presents a comprehensive review on the applications of ML for computer-aided diagnosis (CAD) of PD. We conducted a comprehensive rev...
Improved decisions for unknown behaviours in interactive dynamic influence diagrams [0.03%]
用于交互动态影响图中未知行为的改进决策方法
Yinghui Pan,Mengen Zhou,Biyang Ma et al.
Yinghui Pan et al.
Interactive dynamic influence diagrams (I-DIDs) are a general decision framework for a subject agent who interacts with other agents (of either collaborative or competitive) in a common environment with partial observability. The subject ag...
A survey of NLP methods for oncology in the past decade with a focus on cancer registry applications [0.03%]
近十年来肿瘤学的自然语言处理方法综述及其在癌症登记中的应用
Isaac Hands,Ramakanth Kavuluru
Isaac Hands
Clinical texts from pathology and radiology reports provide critical information for cancer diagnosis and staging. This study surveys the application of natural language processing (NLP) in cancer registry operations from 2014 to 2024. A to...
Comprehensive review of reinforcement learning for medical ultrasound imaging [0.03%]
医学超声成像的强化学习综合回顾
Hanae Elmekki,Saidul Islam,Ahmed Alagha et al.
Hanae Elmekki et al.
Medical Ultrasound (US) imaging has seen increasing demands over the past years, becoming one of the most preferred imaging modalities in clinical practice due to its affordability, portability, and real-time capabilities. However, it faces...
A framework for measuring the training efficiency of a neural architecture [0.03%]
一种衡量神经网络架构训练效率的框架
Eduardo Cueto-Mendoza,John Kelleher
Eduardo Cueto-Mendoza
Measuring Efficiency in neural network system development is an open research problem. This paper presents an experimental framework to measure the training efficiency of a neural architecture. To demonstrate our approach, we analyze the tr...
Contrasting Linguistic Patterns in Human and LLM-Generated News Text [0.03%]
人类与大语言模型生成的新闻文本中的语言模式对比分析
Alberto Muñoz-Ortiz,Carlos Gómez-Rodríguez,David Vilares
Alberto Muñoz-Ortiz
We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different families and four sizes in total. Our analysis spans several...
A review of evaluation approaches for explainable AI with applications in cardiology [0.03%]
可解释人工智能的评估方法在心脏病学中的应用综述
Ahmed M Salih,Ilaria Boscolo Galazzo,Polyxeni Gkontra et al.
Ahmed M Salih et al.
Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI models and is important in building trust in model predictions. XAI explanations themselves require evaluation as to accuracy and reasonableness ...
Knowledge transfer in lifelong machine learning: a systematic literature review [0.03%]
终身机器学习中知识迁移的系统文献综述
Pouya Khodaee,Herna L Viktor,Wojtek Michalowski
Pouya Khodaee
Lifelong Machine Learning (LML) denotes a scenario involving multiple sequential tasks, each accompanied by its respective dataset, in order to solve specific learning problems. In this context, the focus of LML techniques is on utilizing a...
A Comprehensive review of data-driven approaches for forecasting production from unconventional reservoirs: best practices and future directions [0.03%]
用于预测非常规储层产量的数据驱动方法的全面回顾：最佳实践和未来方向
Hamid Rahmanifard,Ian Gates
Hamid Rahmanifard
Prediction of well production from unconventional reservoirs is a complex problem given an incomplete understanding of physics despite large amounts of data. Recently, Data Analytics Techniques (DAT) have emerged as an effective approach fo...