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Results for “generative artificial intelligence”

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At least 235 records · Page 13Linked to original sources

PubMed2001

A feature based pharmacophore for Candida albicans MyristoylCoA: protein N-myristoyltransferase inhibitors.

A three-dimensional pharmacophore model has been generated for Candida albicans MyristoylCoA: protein N-myristoyltransferase (NMT) inhibitors, using the software program CATALYST. The in vitro NMT inhibitory activity of a series of peptidic inhibitors was used for pharmacophore generation. The effect of altering the control parameters and feature selection was studied to arrive at the pharmacophore model. The selection of the best hypothesis model was based on the total cost, predictive ability, difference in the cost from the null hypothesis and alignment of the training set compounds on to the hypothesis. The pharmacophore model selected has four features; one hydrophobic, two hydrogen bond acceptor and one positive ionisable function. Groups identified as necessary by scanning alanine mutagenesis studies of the peptidic substrate of C. albicans NMT, have been identified as pharmacophore features. Comparison of the ligand binding with the enzyme in the crystal structure of NMT and that proposed by the phamacophore is consistent. The pharmacophore thus generated can be used as a template for designing non-peptidic inhibitors of NMT.

Acyltransferases↗

PubMed2004

Data mining in bioinformatics using Weka.

UNLABELLED: The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. AVAILABILITY: http://www.cs.waikato.ac.nz/ml/weka.

Algorithms↗

PubMed2005

Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses.

We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.

Algorithms↗

PubMed2005

Thin compound-eye camera.

An artificial compound-eye objective fabricated by micro-optics technology is adapted and attached to a CMOS sensor array. The novel optical sensor system with an optics thickness of only 0.2 mm is examined with respect to resolution and sensitivity. An optical resolution of 60 x 60 pixels is determined from captured images. The scaling behavior of artificial compound-eye imaging systems is analyzed. Cross talk between channels fabricated by different technologies is evaluated, and the influence on an extension of the field of view by addition of a (Fresnel) diverging lens is discussed. The lithographic generation of opaque walls between channels for optical isolation is experimentally demonstrated.

Animals↗

PubMed2003

New terminology services based on term comparison using semantic definitions and similarity computation.

As medical information can be encoded within different terminological systems, terms comparison is an important issue to allow communication between applications. In description logics, terms are compared by the means of semantic definitions and subsumption relations. Similarity is also a convenient method for term comparison but is not supported by terminology servers which implement subsumption relations. We present new terminology services built on a semantic distance that could help for semantic mediation between medical applications ranging from semi-automatic encoders to data mining tools. These services are 1) comparison between terms 2) k-nearest-neighbors 3) support for concept coding 4) automatic generation of similarity tables 5) distance based queries 6) support for clustering.

Artificial Intelligence↗

PubMed1996

Automatic knowledge acquisition from medical texts.

An approach to knowledge-based understanding of realistic texts from the medical domain (viz. findings of gastro-intestinal diseases) is presented. We survey major methodological features of an object-oriented, fully lexicalized, dependency-based grammar model which is tightly linked to domain knowledge representations based on description logics. The parser adheres to the principles of robustness, incrementality and concurrency. The substrate of automatic knowledge acquisition are text knowledge bases generated by the parser from medical narratives, which represent major portions of the content of these documents.

Artificial Intelligence↗

PubMed1990

Computer-assisted adult medical diagnosis: subject review and evaluation of a new microcomputer-based system.

Three decades after the conceptual foundation was laid for computer-aided diagnosis, some of its potential has been realized. Systems based on probabilistic reasoning have been developed and applied within limited domains (e.g., acute abdominal pain) and for the general diagnosis of systemic disorders. Less progress has been made in the development and application of diagnostic systems based on "artificial intelligence", reflecting theoretical limits to this application of computers to medicine and the enormity of the task. The presently available probabilistic systems have recently been joined by a new microcomputer-based system, MEDITEL Computer-Assisted Diagnosis, Adult System. The performance of this system was evaluated with both clinical-pathologic conference cases and consecutive admissions with undiagnosed illnesses. The correct diagnosis appeared on the list generated by the system in 80 to 90% of the cases. Experience with this and other systems illustrates current issues in the evaluation of computer systems for aid in diagnosis and of computer-based medical "expert" systems in general. These issues include physician acceptance of these systems and the ethical, legal, and regulatory aspects of computer system application. We conclude that, in appropriately selected cases, the accuracy and efficiency of physician diagnosis can be enhanced with computer assistance, and the risk of overlooking the correct diagnosis can be reduced.

Artificial Intelligence↗

PubMed1998

TACHY: an expert system for the management of supraventricular tachycardia in the elderly.

PURPOSE: Many physicians find the management of supraventricular tachyarrhythmia (SVT) in the elderly complex and challenging. With the use of artificial intelligence theory, we developed an interactive computer expert system, TACHY, to recommend therapies and warn physicians of potential therapeutic side effects. METHODS: We developed a knowledge base that stores guidelines for the management of SVT in the elderly. After the diagnosis of current SVT was input into the computer, TACHY generated a list of therapeutic options as hypotheses. TACHY then prompted the user to provide current patient-specific clinical information, and the optimal therapeutic option was then selected. Potential therapeutic side effects were also displayed. TACHY was tested in a retrospective and a prospective study. The retrospective study, comprising 96 patients with 126 episodes of SVT, was performed to determine the concordance of therapy between TACHY and cardiologists. A prospective study in 18 patients with 26 episodes of SVT was also performed to validate TACHY's recommendations in restoring sinus rhythm. RESULTS: In the retrospective study the concordance between TACHY and the cardiologist's first therapeutic option was 95.9% (121 of 126 episodes). In the prospective study sinus rhythm was restored in 18 (69%) of 26 episodes of SVT by the first therapeutic option recommended by TACHY. In the remaining eight episodes use of the second or third suggestion of TACHY was successful in controlling the ventricular response to SVT. No adverse reaction to the therapeutic options suggested by TACHY occurred. CONCLUSION: TACHY, a knowledge-based computer expert system that simulates human decision making, produced promising results in the management of SVT in the elderly.

Aged↗

PubMed1984

Multivariate statistical classification of noisy images (randomly oriented biological macromolecules).

Multivariate Statistical Analysis (MSA) methods have recently been introduced for analyzing images of biological macromolecules [Van Heel and Frank, Ultramicroscopy 6 (1981) 187]. With these techniques, the significant characteristics of each molecular image can be expressed in merely 2 to 8 factorial coordinate values rather than in the typical 64 X 64 = 4096 pixel grey values that originally described the image. This very large reduction in total amount of data facilitates the understanding of the general behavior of a set of molecular images in terms of classes or of general trends in the data set. The (artificial) intelligence of the procedure, however, lies in the decision-making or classification phase. The theory and philosophy of multivariate statistical classification are reviewed using generalized metrics. Problem-dependent classification rationales are proposed. A set of computer-generated "randomly oriented molecular images" are used to test the classification schemes. This model experiment is a step towards 3D structure analysis of macromolecules based on large numbers of (noisy) electron microscopical images of randomly oriented biological macromolecules.

Animals↗

PubMedDate not supplied

An expert system for the diagnosis of epilepsy: results of a clinical trial.

BACKGROUND: Artificial intelligence is an area where computer systems are used to solve real-life problems that require expert human intelligence. Expert systems serve as an effective alternative to supplement the dearth of human experts in a narrow domain of applications. We developed an expert system named SEIZ using DIAGNOS (an expert system shell for diagnostic applications) for the diagnosis and management of epilepsy. METHODS: A clinical trial was done to test the reliability of SEIZ. The clinical and demographic data from the medical records of 50 patients with epilepsy who attended an epilepsy clinic were provided to the expert system. The system-generated diagnosis was compared with the clinical diagnosis. RESULTS: The seizure types and epileptic syndromes for the 50 patients included generalized -tonic-clonic seizure (14), absence (4), complex partial seizure (18), simple partial seizure (4), juvenile myoclonic epilepsy (5) and other epileptic syndromes (3). There were two cases of hysterical conversion reaction. There was concordance in the diagnosis between the expert system and clinician in 47 cases (94%). The overall sensitivity was 94% and the specificity was 100% for absence, generalized tonic-clonic seizures, simple partial seizures and juvenile myoclonic epilepsy; 94% for complex partial seizures and 98% for hysterical conversion reaction. CONCLUSION: This expert system could generate reliable diagnoses for patients with epilepsy. Such a system may be useful for a doctor in a remote or peripheral area where an expert on epilepsy is not available.

Adult↗

PubMed2005

Interpolation artefacts in non-rigid registration.

Voxel based non-rigid registration of images involves finding a similarity maximising transformation that deforms a source image to the coordinate system of a target image. In order to do this, interpolation is required to estimate the source intensity values corresponding to transformed target voxels. These interpolated source intensities are used when calculating the similarity measure being optimised. In this work, we compare the extent and nature of artefactual displacements produced by voxel based non-rigid registration techniques for different interpolators and investigate their relationship to image noise and global transformation error. A per-voxel similarity gradient is calculated and the resulting vector field is used to characterise registration artefacts for each interpolator. Finally, we show that the resulting registration artefacts can generate spurious volume changes for image pairs with no expected volume change.

Algorithms↗

PubMed2005

Implementation of high-dimensional feature map for segmentation of MR images.

A method that considerably reduces the computational and memory complexities associated with the generation of high-dimensional (> or =3) feature maps for image segmentation is described. The method is based on the K-nearest neighbor (KNN) classification and consists of two parts: preprocessing of feature space and fast KNN. This technique is implemented on a PC and applied for generating 3D and 4D feature maps for segmenting MR brain images of multiple sclerosis patients.

Algorithms↗

PubMed1997

DIAVAL, a Bayesian expert system for echocardiography.

DIAVAL is an expert system for the diagnosis of heart diseases, including several kinds of data, mainly from echocardiography. The first part of this paper is devoted to the causal probabilistic model which constitutes the knowledge base of the expert system in the form of a Bayesian network, emphasizing the importance of the OR gate. The second part deals with the process of diagnosis, which consists of computing the a posteriori probabilities, selecting the most probable and most relevant diagnoses, and generating a written report. It also describes the results of the evaluation of the program.

Artificial Intelligence↗

PubMed2006

Unsupervised contour closure algorithm for range image edge-based segmentation.

This paper presents an efficient technique for extracting closed contours from range images' edge points. Edge points are assumed to be given as input to the algorithm (i.e., previously computed by an edge-based range image segmentation technique). The proposed approach consists of three steps. Initially, a partially connected graph is generated from those input points. Then, the minimum spanning tree of that graph is computed. Finally, a postprocessing technique generates a single path through the regions' boundaries by removing noisy links and closing open contours. The novelty of the proposed approach lies in the fact that, by representing edge points as nodes of a partially connected graph, it reduces the contour closure problem to a minimum spanning tree partitioning problem plus a cost function minimization stage to generate closed contours. Experimental results with synthetic and real range images, together with comparisons with a previous technique, are presented.

Algorithms↗

PubMed2005

Vessel tree reconstruction in thoracic CT scans with application to nodule detection.

Vessel tree reconstruction in volumetric data is a necessary prerequisite in various medical imaging applications. Specifically, when considering the application of automated lung nodule detection in thoracic computed tomography (CT) scans, vessel trees can be used to resolve local ambiguities based on global considerations and so improve the performance of nodule detection algorithms. In this study, a novel approach to vessel tree reconstruction and its application to nodule detection in thoracic CT scans was developed by using correlation-based enhancement filters and a fuzzy shape representation of the data. The proposed correlation-based enhancement filters depend on first-order partial derivatives and so are less sensitive to noise compared with Hessian-based filters. Additionally, multiple sets of eigenvalues are used so that a distinction between nodules and vessel junctions becomes possible. The proposed fuzzy shape representation is based on regulated morphological operations that are less sensitive to noise. Consequently, the vessel tree reconstruction algorithm can accommodate vessel bifurcation and discontinuities. A quantitative performance evaluation of the enhancement filters and of the vessel tree reconstruction algorithm was performed. Moreover, the proposed vessel tree reconstruction algorithm reduced the number of false positives generated by an existing nodule detection algorithm by 38%.

Adult↗

PubMed2007

Characteristics and value of machine learning for imaging in high content screening.

Requirements for a flexible image analysis package for high content screening (HCS) are discussed. An overview of tools and techniques for image analysis and machine learning is given. Machine learning for classification and segmentation, the two fundamental elements of image analysis, is discussed. Next generation image analysis packages for HCS are reviewed. Recommendations for the development of image analysis solutions for advanced assays are given.

Artificial Intelligence↗

PubMed2003

Use of latent semantic analysis for predicting psychological phenomena: two issues and proposed solutions.

Latent semantic analysis (LSA) is a computational model of human knowledge representation that approximates semantic relatedness judgments. Two issues are discussed that researchers must attend to when evaluating the utility of LSA for predicting psychological phenomena. First, the role of semantic relatedness in the psychological process of interest must be understood. LSA indices of similarity should then be derived from this theoretical understanding. Second, the knowledge base (semantic space) from which similarity indices are generated must contain 'knowledge' that is appropriate to the task at hand. Proposed solutions are illustrated with data from an experiment in which LSA-based indices were generated from theoretical analysis of the processes involved in understanding two conflicting accounts of a historical event. These indices predict the complexity of subsequent student reasoning about the event, as well as hand-coded predictions generated from think-aloud protocols collected when students were reading the accounts of the event.

Adolescent↗

PubMed1994

The management of information: storage and retrieval of data.

Internationally harmonized and cost-effective control of chemicals marketed worldwide greatly depend both on the generation of and easy access to reliable and comparable experimental information. Stored data are of use only if information can be retrieved quickly in an understandable form. Some models and theories of information retrieval (e.g. fuzzy set theory, probabilistic approach, artificial intelligence) are briefly discussed first, then followed by applications (such as indexing and clustering techniques). Finally the structure of databases is briefly reviewed.

Database Management Systems↗