Abstract:
:As a crucial step of biological event extraction, event trigger identification has attracted much attention in recent years. Deep representation methods, which have the superiorities of less feature engineering and end-to-end training, show better performance than statistical methods. While most deep learning methods have been done on sentence-level event extraction, there are few works taking document context into account, losing potentially informative knowledge that is beneficial for trigger detection. In this paper, we propose a variational neural approach for biomedical event extraction, which can take advantage of latent topics underlying documents. By adopting a joint modeling manner of topics and events, our model is able to produce more meaningful and event-indicative words compare to prior topic models. In addition, we introduce a language model embeddings to capture context-dependent features. Experimental results show that our approach outperforms various baselines in a commonly used multi-level event extraction corpus.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
Zhang J,Liu M,Zhang Ydoi
10.1016/j.artmed.2019.101783subject
Has Abstractpub_date
2020-03-01 00:00:00pages
101783eissn
0933-3657issn
1873-2860pii
S0933-3657(19)30923-6journal_volume
103pub_type
杂志文章abstract:OBJECTIVE:High dose radiation has been well known for increasing the risk of carcinogenesis. However, the understanding of biological effects of low dose radiation is limited. Low dose radiation is reported to affect several signaling pathways including deoxyribonucleic acid repair, survival, cell cycle, cell growth, a...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2010.04.001
更新日期:2010-07-01 00:00:00
abstract:BACKGROUND:Motor vehicle accidents (MVA) represent a significant burden on health systems globally. Tens of thousands of people are injured in Australia every year and may experience significant disability. Associated economic costs are substantial. There is little literature on the health service utilization patterns ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2020.101997
更新日期:2021-01-01 00:00:00
abstract::Electronic medical records (EMRs) contain a wealth of knowledge that can be used to assist doctors in making clinical decisions like disease diagnosis. Constructing a medical knowledge network (MKN) to link medical concepts in EMRs is an effective way to manage this knowledge. The quality of the diagnostic result made...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2020.101927
更新日期:2020-07-01 00:00:00
abstract::Traditional Chinese medicine has developed over more than 4000 years. A tremendous amount of medical knowledge has been accumulated, among which herbal drugs and formulae are an important portion. This paper presents an ontology for traditional Chinese drugs and formulae, and an ontology-based system for extracting kn...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.01.015
更新日期:2004-09-01 00:00:00
abstract::In this paper we describe how we generated written explanations to 'indirect users' of a knowledge-based system in the domain of drug prescription. We call 'indirect users' the intended recipients of explanations, to distinguish them from the prescriber (the 'direct' user) who interacts with the system. The Explanatio...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/0933-3657(95)00029-1
更新日期:1996-05-01 00:00:00
abstract:OBJECTIVES:We present in this article experiments on multi-language information extraction and access in the medical domain. For such applications, multilingual terminology plays a crucial role when working on specialized languages and specific domains. MATERIAL AND METHODS:We propose firstly a method for enriching mu...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.07.015
更新日期:2005-02-01 00:00:00
abstract::Manual delineation of vestibular schwannoma (VS) by magnetic resonance (MR) imaging is required for diagnosis, radiosurgery dose planning, and follow-up tumor volume measurement. A rapid and objective automatic segmentation method is required, but problems have been encountered due to the low through-plane resolution ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2020.101911
更新日期:2020-07-01 00:00:00
abstract:BACKGROUND:The current situation of critical progression in resistance to more effective antibiotics has forced the reuse of old highly toxic antibiotics and, for several reasons, the extension of the indications of combined antibiotic therapy as alternative options to broad spectrum empirical mono-therapy. A key aspec...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2019.101751
更新日期:2020-01-01 00:00:00
abstract:OBJECTIVE:Connect-Four, a new sensorimotor rhythm (SMR) based brain-computer interface (BCI) gaming application, was evaluated by four severely motor restricted end-users; two were in the locked-in state and had unreliable eye-movement. METHODS:Following the user-centred approach, usability of the BCI prototype was ev...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2013.08.001
更新日期:2013-10-01 00:00:00
abstract::A new algorithm for neural network pruning is presented. Using this algorithm, networks with small number of connections and high accuracy rates for breast cancer diagnosis are obtained. We will then describe how rules can be extracted from a pruned network by considering only a finite number of hidden unit activation...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/0933-3657(95)00019-4
更新日期:1996-02-01 00:00:00
abstract::A capsule endoscopy examination of the human small bowel generates a large number of images that have high similarity. In order to reduce the time it takes to review the high similarity images, clinicians will increase the playback speed, typically to 15 frames per second [1]. Associated with this behaviour is an incr...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2018.12.008
更新日期:2019-03-01 00:00:00
abstract::Abnormalities in the organization of brain circuits may underlie many types of epilepsy. This hypothesis can best be evaluated in the case of temporal lobe epilepsy, where evidence of rewiring (synaptic reorganization) can be found in the dentate gyrus. Computer modeling of normal and reorganized dentate gyrus was use...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(98)00005-0
更新日期:1998-05-01 00:00:00
abstract:OBJECTIVE:The objective of this paper is to classify 3D medical images by analyzing spatial distributions to model and characterize the arrangement of the regions of interest (ROIs) in 3D space. METHODS AND MATERIAL:Two methods are proposed for facilitating such classification. The first method uses measures of simila...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.07.001
更新日期:2005-03-01 00:00:00
abstract::Computer-aided detection (CADe) systems play a crucial role in pulmonary nodule detection via chest radiographs (CXRs). A two-stage CADe scheme usually includes nodule candidate detection and false positive reduction. A pure deep learning model, such as faster region convolutional neural network (faster R-CNN), has be...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2020.101881
更新日期:2020-07-01 00:00:00
abstract:OBJECTIVE:We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer decision support system, oncologists can obtain powerful information or knowledge, complementing their own experiential knowledge, in their m...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2017.02.003
更新日期:2017-03-01 00:00:00
abstract:OBJECTIVE:To assess whether a user-centred prototype clinical decision support system (CDSS) providing patient-specific advice better supports healthcare practitioners in terms of (a) types of usability problems detected and (b) effective and efficient retrieval of childhood cancer survivor's follow-up screening proced...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2013.04.004
更新日期:2013-09-01 00:00:00
abstract:OBJECTIVE:A major focus in computational system biology research is defining organizing principles that govern complex biological network formation and evolution. The task is considered a major challenge because network behavior and function prediction requires the identification of functionally and statistically impor...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2007.07.006
更新日期:2007-10-01 00:00:00
abstract::Case-based approaches predict the behaviour of dynamic systems by analysing a given experimental setting in the context of others. To select similar cases and to control adaptation of cases, they employ general knowledge. If that is neither available nor inductively derivable, the knowledge implicit in cases can be ut...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(98)00057-8
更新日期:1999-03-01 00:00:00
abstract:OBJECTIVE:Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden S...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2015.09.003
更新日期:2018-11-01 00:00:00
abstract:OBJECTIVE:New medical systems may be rejected by staff because they do not integrate with local practice. An expert system, FLORENCE, is being developed to help staff in a neonatal intensive care unit (NICU) make decisions about ventilator settings when treating babies with respiratory distress syndrome. For FLORENCE t...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2005.01.004
更新日期:2005-11-01 00:00:00
abstract::The optical device LIPOMETER allows for non-invasive, quick, precise and safe determination of subcutaneous fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top). In this paper, we show how the high-dimensional SAT-Top information of women with type-2 diabetes mellitus (non-insulin-dependent dia...
journal_title:Artificial intelligence in medicine
pub_type: 临床试验,杂志文章
doi:10.1016/s0933-3657(99)00017-2
更新日期:1999-10-01 00:00:00
abstract:BACKGROUND:After several years of treatment, patients with Parkinson's disease (PD) tend to have, as a side effect of the medication, dyskinesias. Close monitoring may benefit patients by enabling doctors to tailor a personalised medication regimen. Moreover, dyskinesia monitoring can help neurologists make more inform...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2016.01.001
更新日期:2016-02-01 00:00:00
abstract:OBJECTIVE:The aim of this paper is to study the feasibility and the performance of some classifier systems belonging to family of instance-based (IB) learning as second-opinion diagnostic tools and as tools for the knowledge extraction phase in the process of knowledge discovery in clinical databases. MATERIALS AND ME...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2011.04.002
更新日期:2011-07-01 00:00:00
abstract:OBJECTIVE:Our goal is to propose and solve a new formulation of the recently-formalized patient admission scheduling problem, extending it by including several real-world features, such as the presence of emergency patients, uncertainty in the length of stay, and the possibility of delayed admissions. METHOD:We devise...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2012.09.001
更新日期:2012-11-01 00:00:00
abstract::The advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming. It is expected to spread as an epidemic by 2030. Present methods of determining the health of one's heart include doppler based echocardiogram, MDCT (Multi Detector Computed Tomography), among various other invasive an...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2019.02.002
更新日期:2019-05-01 00:00:00
abstract:OBJECTIVE:We present a combined terminological resource for text mining over biomedical literature. The purpose of the resource is to allow the detection of mentions of specific biological entities in scientific publications, and their grounding to widely accepted identifiers. This is an essential process, useful in it...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2011.04.011
更新日期:2011-06-01 00:00:00
abstract:OBJECTIVE:We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis regulation. METHODS:We cast both models and background knowledge in terms of processes that interact to account for behavior. We a...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2006.04.003
更新日期:2006-07-01 00:00:00
abstract:BACKGROUND AND MOTIVATION:DNA microarray technology has made it possible to determine the expression levels of thousands of genes in parallel under multiple experimental conditions. Genome-wide analyses using DNA microarrays make a great contribution to the exploration of the dynamic state of genetic networks, and furt...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2005.02.007
更新日期:2005-09-01 00:00:00
abstract:OBJECTIVE:In the last few years several complete genome sequences have been made available to the research community. The annotation of their complete inventory of protein coding genes, however, has been so far an elusive goal. Classical ab initio gene prediction methods have been of great support for this task, but sh...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2008.07.015
更新日期:2009-02-01 00:00:00
abstract::We introduce a novel approach to couple temporal similarity with spatial neighborhood information. This is achieved by concatenating the K nearest, spatially contiguous neighbors of a pixel time-course (TC) of T time-instances. This produces a new TC of (K+1)T time instances. Depending on how "nearest" is defined, we ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(02)00005-2
更新日期:2002-05-01 00:00:00