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 also describe IPM, an algorithm for inducing quantitative process models from such input. RESULTS:We demonstrate IPM's use both on photosynthesis and on a second domain, biochemical kinetics, reporting the models induced and their fit to observations. CONCLUSION:We consider the generality of our approach, discuss related research on biological modeling, and suggest directions for future work.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
Langley P,Shiran O,Shrager J,Todorovski L,Pohorille Adoi
10.1016/j.artmed.2006.04.003subject
Has Abstractpub_date
2006-07-01 00:00:00pages
191-201issue
3eissn
0933-3657issn
1873-2860pii
S0933-3657(06)00061-3journal_volume
37pub_type
杂志文章abstract：OBJECTIVE:A metaschema is an abstraction network of the UMLS's semantic network (SN) obtained from a connected partition of its collection of semantic types. A lexical metaschema was previously derived based on a lexical partition which partitioned the SN into semantic-type groups using identical word-usage among the n...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.01.002
更新日期：2005-07-01 00:00:00
abstract：:Successful secondary structure predictions provide a starting point for direct tertiary structure modelling, and also can significantly improve sequence analysis and sequence-structure threading for aiding in structure and function determination. Hence the improvement of predictive accuracy of the secondary structure ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2004.01.009
更新日期：2004-06-01 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：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:We explore the link between dataset complexity, determining how difficult a dataset is for classification, and classification performance defined by low-variance and low-biased bolstered resubstitution error made by k-nearest neighbor classifiers. METHODS AND MATERIAL:Gene expression based cancer classificat...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.08.004
更新日期：2009-02-01 00:00:00
abstract：:Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to peri...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2017.06.008
更新日期：2017-06-01 00:00:00
abstract：:Artificial intelligence (AI) will pave the way to a new era in medicine. However, currently available AI systems do not interact with a patient, e.g., for anamnesis, and thus are only used by the physicians for predictions in diagnosis or prognosis. However, these systems are widely used, e.g., in diabetes or cancer p...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.101706
更新日期：2019-09-01 00:00:00
abstract：OBJECTIVE:One of the major topics towards robot consciousness is to give a robot the capabilities of self-consciousness. We propose that robot self-consciousness is based on higher order perception of the robot, in the sense that first-order robot perception is the immediate perception of the outer world, while higher ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.07.003
更新日期：2008-10-01 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：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：OBJECTIVES:Brain-computer interfaces (BCIs) are no longer only used by healthy participants under controlled conditions in laboratory environments, but also by patients and end-users, controlling applications in their homes or clinics, without the BCI experts around. But are the technology and the field mature enough f...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2013.08.004
更新日期：2013-10-01 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：:Deregulated splicing machinery components have shown to be associated with the development of several types of cancer and, therefore, the determination of such alterations can help the development of tumor-specific molecular targets for early prognosis and therapy. Determining such splicing components, however, is not...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101950
更新日期：2020-08-01 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：OBJECTIVE:The objective of the present work was to develop and compare methods for automatic detection of bilateral sleep spindles. METHODS AND MATERIALS:All-night sleep electroencephalographic (EEG) recordings of 12 healthy subjects with a median age of 40 years were studied. The data contained 6043 visually scored b...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2007.04.003
更新日期：2007-07-01 00:00:00
abstract：:In a digitally enabled healthcare setting, we posit that an individual's current location is pivotal for supporting many virtual care services-such as tailoring educational content towards an individual's current location, and, hence, current stage in an acute care process; improving activity recognition for supportin...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101931
更新日期：2020-08-01 00:00:00
abstract：:Allowing exchange of information and cooperation among network-wide distributed and heterogeneous applications is a major need of current health-care information systems. The European project SynEx aims at developing an integration platform for both new and legacy applications on each partner's site. We developed, in ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(03)00007-1
更新日期：2003-03-01 00:00:00
abstract：OBJECTIVE:This paper proposes a novel method for the extraction and classification of individual motor unit action potentials (MUAPs) from intramuscular electromyographic signals. METHODOLOGY:The proposed method automatically detects the number of template MUAP clusters and classifies them into normal, neuropathic or ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.09.002
更新日期：2006-05-01 00:00:00
abstract：:To explore the design of computer-supported collaborative work in health care, a case study is described addressing the social contexts and conditions influencing the development process. The data set covers 13 consecutive meetings held in a systems design group over a 2-year period, in total approximately 24 h of vid...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(97)00046-8
更新日期：1998-02-01 00:00:00
abstract：BACKGROUND:Patients who are readmitted to an intensive care unit (ICU) usually have a high risk of mortality and an increased length of stay. ICU readmission risk prediction may help physicians to re-evaluate the patient's physical conditions before patients are discharged and avoid preventable readmissions. ICU readmi...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2018.08.004
更新日期：2019-04-01 00:00:00
abstract：OBJECTIVE:Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data management system (PDMS) at our local intensive care units does not native...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2015.09.009
更新日期：2018-11-01 00:00:00
abstract：:According to functional or anatomical modalities, medical imaging provides a visual representation of complex structures or activities in the human body. One of the most common processing methods applied to those images is segmentation, in which an image is divided into a set of regions of interest. Human anatomical c...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101980
更新日期：2020-11-01 00:00:00
abstract：:In case-based studies, controls are retrospectively assigned to patients in order to permit a statistical evaluation of the study results through a comparison of the main outcome measures for the patient and retrieved control groups. Inappropriate selection of the controls by using false retrieval parameters or a fals...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(02)00084-2
更新日期：2002-11-01 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：:Rough sets (Pawlak Z. Rough Sets: Theoretical Aspects of Reasoning about Data, Dordrecht: Kluwer Academic Publishers, 1991) is a relatively new approach to representing and reasoning with incomplete and uncertain knowledge. This article introduces the basic concepts of rough sets and Boolean reasoning (Brown FM. Boole...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(98)00051-7
更新日期：1999-02-01 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：:This paper presents a computer-based model for differential diagnosis of specific language impairment (SLI), a language disorder that, in many cases, cannot be easily diagnosed. This difficulty necessitates the development of a methodology to assist the speech therapist in the diagnostic process. The methodology tool ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(02)00076-3
更新日期：2003-11-01 00:00:00
abstract：:In this paper, we propose an approach for managing clinical guidelines. We outline a modular architecture, allowing us to separate two conceptually distinct aspects: the representation (and acquisition) of clinical guidelines and their execution. We propose an expressive formalism, which allows one to deal with the co...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章,评审
doi：10.1016/s0933-3657(01)00087-2
更新日期：2001-11-01 00:00:00
abstract：OBJECTIVE:The successful preparation of cells for therapy depends on the characterization of causal factors affecting cell quality. Ultra scale-down methods are used to characterize cells in terms of their response to process engineering causal factors of hydrodynamic shear stress and time. This response is in turn cha...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2014.07.003
更新日期：2014-10-01 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
