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 traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. METHODS AND MATERIAL:An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. RESULTS:Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. CONCLUSIONS:Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
He Y,Hui SCdoi
10.1016/j.artmed.2009.03.004subject
Has Abstractpub_date
2009-10-01 00:00:00pages
105-19issue
2eissn
0933-3657issn
1873-2860pii
S0933-3657(09)00054-2journal_volume
47pub_type
杂志文章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：:In this contribution we present an application of a knowledge-based neural network technique in the domain of medical research. We consider the crucial problem of intensive care patients developing a septic shock during their stay at the intensive care unit. Septic shock is of prime importance in intensive care medici...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(03)00057-5
更新日期：2003-06-01 00:00:00
abstract：:Pressure injuries represent a tremendous healthcare challenge in many nations. Elderly and disabled people are the most affected by this fast growing disease. Hence, an accurate diagnosis of pressure injuries is paramount for efficient treatment. The characteristics of these wounds are crucial indicators for the progr...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.101742
更新日期：2020-01-01 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：: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：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：:Disagreement or inconsistencies in mammographic interpretation motivates utilizing computerized pattern recognition algorithms to aid the assessment of radiographic features. We have studied the potential for using artificial neural networks (ANNs) to analyze interpreted radiographic features from film screen mammogra...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(98)00040-2
更新日期：1998-11-01 00:00:00
abstract：OBJECTIVE:To use the detection of clinically relevant inconsistencies to support the reasoning capabilities of intelligent agents acting as physicians and tutors in the realm of clinical medicine. METHODS:We are developing a cognitive architecture, OntoAgent, that supports the creation and deployment of intelligent ag...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2012.04.005
更新日期：2012-07-01 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：:INTERNIST-I was an expert system designed in the early 1970's to diagnose multiple diseases in internal medicine by modelling the behaviour of clinicians. Its form and operation are described, and evaluations of the system are surveyed. The major result of the project was its knowledge base which has been used in succ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/0933-3657(94)00028-q
更新日期：1995-04-01 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
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：: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:The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining technology to analyze and predict the depression tendency of web posts. ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2015.10.003
更新日期：2016-01-01 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: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：: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:This work proposes creating an automatic system to locate and segment the optic nerve head (ONH) in eye fundus photographic images using genetic algorithms. METHODS AND MATERIAL:Domain knowledge is used to create a set of heuristics that guide the various steps involved in the process. Initially, using an ey...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.04.005
更新日期：2008-07-01 00:00:00
abstract：:Incorporating prior knowledge into black-box classifiers is still much of an open problem. We propose a hybrid Bayesian methodology that consists in encoding prior knowledge in the form of a (Bayesian) belief network and then using this knowledge to estimate an informative prior for a black-box model (e.g. a multilaye...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(03)00053-8
更新日期：2003-09-01 00:00:00
abstract：:The automated analysis of retinal images is a widely researched area which can help to diagnose several diseases like diabetic retinopathy in early stages of the disease. More specifically, separation of vessels and lesions is very critical as features of these structures are directly related to the diagnosis and trea...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.07.010
更新日期：2019-08-01 00:00:00
abstract：:In this study different substitution methods for the replacement of missing data values were inspected for the use of these cases in a neural network based decision support system for acute appendicitis. The leucocyte count had the greatest number of missing values and was used in the analyses. Four different methods ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(98)00027-x
更新日期：1998-07-01 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：: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：: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：:This work presents a hybrid expert system (HES) intended to minimise some complex problems pervasive to knowledge engineering such as: the knowledge elicitation process, known as the bottleneck of expert systems; the choice of a model for knowledge representation to codify human reasoning; the number of neurons in the...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(00)00090-7
更新日期：2001-01-01 00:00:00
abstract：OBJECTIVE:Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that the boundaries between classes of patients or classes of functionally related genes are sometimes not clearly defined. The ma...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.07.014
更新日期：2009-02-01 00:00:00
abstract：:Medical diagnosis and therapy planning at modern intensive care units (ICUs) have been refined by the technical improvement of their equipment. However, the bulk of continuous data arising from complex monitoring systems in combination with discontinuously assessed numerical and qualitative data creates a rising infor...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(96)00355-7
更新日期：1996-11-01 00:00:00
abstract：OBJECTIVE:Coronary artery disease has been described as one of the curses of the western world, as it is one of its most important causes of mortality. Therefore, clinicians seek to improve diagnostic procedures, especially those that allow them to reach reliable early diagnoses. In the clinical setting, coronary arter...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2011.04.009
更新日期：2011-06-01 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：: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
