Abstract：
OBJECTIVES:The existence of proper non-invasive temperature estimators is an essential aspect when thermal therapy applications are envisaged. These estimators must be good predictors to enable temperature estimation at different operational situations, providing better control of the therapeutic instrumentation. In this work, radial basis functions artificial neural networks were constructed to access temperature evolution on an ultrasound insonated medium. METHODS:The employed models were radial basis functions neural networks with external dynamics induced by their inputs. Both the most suited set of model inputs and number of neurons in the network were found using the multi-objective genetic algorithm. The neural models were validated in two situations: the operating ones, as used in the construction of the network; and in 11 unseen situations. The new data addressed two new spatial locations and a new intensity level, assessing the intensity and space prediction capacity of the proposed model. RESULTS:Good performance was obtained during the validation process both in terms of the spatial points considered and whenever the new intensity level was within the range of applied intensities. A maximum absolute error of 0.5 degrees C+/-10% (0.5 degrees C is the gold-standard threshold in hyperthermia/diathermia) was attained with low computationally complex models. CONCLUSION:The results confirm that the proposed neuro-genetic approach enables foreseeing temperature propagation, in connection to intensity and space parameters, thus enabling the assessment of different operating situations with proper temperature resolution.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
Teixeira CA,Ruano MG,Ruano AE,Pereira WCdoi
10.1016/j.artmed.2008.03.008subject
Has Abstractpub_date
2008-06-01 00:00:00pages
127-39issue
2eissn
0933-3657issn
1873-2860pii
S0933-3657(08)00037-7journal_volume
43pub_type
杂志文章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：:HepatoConsult is a publicly available knowledge-based second opinion and documentation system aiding in the diagnosis of liver diseases. The positive results of a prospective diagnostic evaluation study encouraged its use in clinical routine, although the available hardware infrastructure was not optimal. The comments...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(01)00104-x
更新日期：2002-03-01 00:00:00
abstract：:As part of a plan to promote semi-automatic knowledge acquisition for the medical consultant system CADIAG-II/RHEUMA, this study sought to explore and cope with the variability of results that may be anticipated when performing knowledge acquisition with patient data from different patient settings. Patient data were ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(02)00025-8
更新日期：2002-07-01 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：: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 ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.101783
更新日期：2020-03-01 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：: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：:Over the years, there has been growing interest in using machine learning techniques for biomedical data processing. When tackling these tasks, one needs to bear in mind that biomedical data depends on a variety of characteristics, such as demographic aspects (age, gender, etc.) or the acquisition technology, which mi...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101804
更新日期：2020-03-01 00:00:00
abstract：OBJECTIVE:Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2009.03.004
更新日期：2009-10-01 00:00:00
abstract：MOTIVATION:Prescribing cascade (PC) occurs when an adverse drug reaction (ADR) is misinterpreted as a new medical condition, leading to further prescriptions for treatment. Additional prescriptions, however, may worsen the existing condition or introduce additional adverse effects (AEs). Timely detection and prevention...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2016.06.002
更新日期：2016-07-01 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：:Multichannel transcranial magnetic stimulation (mTMS) is a therapeutic method to improve psychiatric diseases, which has a flexible working pattern used to different applications. In order to make the electric field distribution in the brain meet the treatment expectations, we have developed a novel multi-swam particl...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101790
更新日期：2020-04-01 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：OBJECTIVES:The objective of this study is to devise a modelling strategy for attaining in-silico models replicating human physiology and, in particular, the activity of the autonomic nervous system. METHOD:Discrete Multiphysics (a multiphysics modelling technique) and Reinforcement Learning (a Machine Learning algorit...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.06.005
更新日期：2019-07-01 00:00:00
abstract：OBJECTIVE:Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2014.06.003
更新日期：2014-09-01 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：:We describe an approach for developing knowledge-based medical decision support systems based on the new technology of case-based reasoning. This work is based on the results of the Inreca European project and preliminary results from the Inreca + project which mainly deals with medical applications. One goal was to s...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(97)00038-9
更新日期：1998-01-01 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：OBJECTIVES:Access to the world wide web and multimedia content is an important aspect of life. We present a web browser and a multimedia user interface adapted for control with a brain-computer interface (BCI) which can be used by severely motor impaired persons. METHODS:The web browser dynamically determines the most...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2014.12.001
更新日期：2015-01-01 00:00:00
abstract：OBJECTIVE:In this paper, we aim to evaluate the use of electronic technologies in out of hours (OoH) task-management for assisting the design of effective support systems in health care; targeting local facilities, wards or specific working groups. In addition, we seek to draw and validate conclusions with relevance to...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2016.09.005
更新日期：2016-10-01 00:00:00
abstract：OBJECTIVE:In this paper, we extend a preliminary proposal and discuss in a deeper and more formal way an approach to evaluate temporal similarity between clinical workflow cases (i.e., executions of clinical processes). More precisely, we focus on (i) the representation of clinical processes by using a temporal concept...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.07.013
更新日期：2009-05-01 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：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:In this paper, we propose a novel algorithm to extract the active intervals of intracardiac electrograms during atrial fibrillation. METHODS:First, we show that the characteristics of the signal waveform at its inflection points are prominent features that are implicitly used by human annotators for distingu...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2018.02.003
更新日期：2018-04-01 00:00:00
abstract：OBJECTIVE:Protein homology prediction between protein sequences is one of critical problems in computational biology. Such a complex classification problem is common in medical or biological information processing applications. How to build a model with superior generalization capability from training samples is an ess...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.02.003
更新日期：2005-09-01 00:00:00
abstract：:This paper describes a methodology for achieving an efficient implementation of clinical practice guidelines. Three main steps are illustrated: knowledge representation, model simulation and implementation within a health care organisation. The resulting system can be classified as a 'guideline-based careflow manageme...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(00)00050-6
更新日期：2000-08-01 00:00:00
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：AIM:A new automatic method for detecting specific points and lines (straight and curves) in dental panoramic radiographies (orthopantomographies) is proposed, where the human knowledge is mapped to the automatic system. The goal is to compute relevant mandibular indices (Mandibular Cortical Width, Panoramic Mandibular ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101816
更新日期：2020-03-01 00:00:00
abstract：:During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2018.02.001
更新日期：2018-04-01 00:00:00
abstract：:Quality of life of patients with Parkinson's disease degrades significantly with disease progression. This paper presents a step towards personalized management of Parkinson's disease patients, based on discovering groups of similar patients. Similarity is based on patients' medical conditions and changes in the presc...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2018.04.010
更新日期：2018-09-01 00:00:00
