Results 71 to 80 of about 131,254 (287)
Neural Document Expansion with User Feedback [PDF]
, 2019 This paper presents a neural document expansion approach (NeuDEF) that enriches document representations for neural ranking models. NeuDEF harvests expansion terms from queries which lead to clicks on the document and weights these expansion terms with learned attention. It is plugged into a standard neural ranker and learned end-to-end. Experiments on
arxiv +1 more source
FEBS Open Bio, EarlyView.The tumor microenvironment is a dynamic, multifaceted complex system of interdependent cellular, biochemical, and biophysical components. Three‐dimensional in vitro models of the tumor microenvironment enable a better understanding of these interactions and their impact on cancer progression and therapeutic resistance.
Salma T. Rafik +3 more
wiley +1 more source
FEBS Open Bio, EarlyView.We generated and characterized clear cell renal cell carcinoma models using the patient‐derived RCC243 cell line—including cell culture, orthotopic, and metastatic tumors—via single‐cell RNA‐sequencing for comparisons between models and patient tumor datasets.
Richard Huang +9 more
wiley +1 more source
Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks
IEEE Access, 2019 Location search and recommendation have received significant attention in recent years. To protect the users' privacy, we propose and study a novel privacy-protected route-based spatial-textual location (PPRSTL) query in road networks.
Hongwei Liu +3 more
doaj +1 more source
FEBS Open Bio, EarlyView.Long non‐coding RNAs (lncRNAs) occupy an abundant fraction of the eukaryotic transcriptome and an emerging area in cancer research. Regulation by lncRNAs is based on their subcellular localization in HNSCC. This cartoon shows the various functions of lncRNAs in HNSCC discussed in this review.
Ellen T. Tran +3 more
wiley +1 more source
Exploring Query Categorisation for Query Expansion: A Study [PDF]
arXiv, 2015 The vocabulary mismatch problem is one of the important challenges facing traditional keyword-based Information Retrieval Systems. The aim of query expansion (QE) is to reduce this query-document mismatch by adding related or synonymous words or phrases to the query.
arxiv
Deep Reinforced Query Reformulation for Information Retrieval [PDF]
arXiv, 2020 Query reformulations have long been a key mechanism to alleviate the vocabulary-mismatch problem in information retrieval, for example by expanding the queries with related query terms or by generating paraphrases of the queries. In this work, we propose a deep reinforced query reformulation (DRQR) model to automatically generate new reformulations of ...
arxiv
A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
Cloud Information Retrieval: Model Description and Scheme Design
IEEE Access, 2018 The fast development of cloud technology has brought about a new trend in the field of information service: more and more information is being transferred to the cloud as requested.
Zhen Yang, Jiliang Tang, Huan Liu
doaj +1 more source
Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Purpose Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re‐optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high‐quality plan within time constraints remains a common barrier.
Sean J. Domal +9 more
wiley +1 more source