SEARCH · PubMed Health

Results for “generative artificial intelligence”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20Linked to original sources

PubMed2005

Automatic navigation path generation based on two-phase adaptive region-growing algorithm for virtual angioscopy.

In this paper, we propose a fast and automated navigation path generation algorithm to visualize inside of carotid artery using MR angiography images. The carotid artery is one of the body regions not accessible by real optical probe but can be visualized with virtual endoscopy. By applying two-phase adaptive region-growing algorithm, the carotid artery segmentation is started at the initial seed, which is located on the initially thresholded binary image. This segmentation algorithm automatically detects the branch position with stack feature. Combining with a priori knowledge of anatomic structure of carotid artery, the detected branch position is used to separate the carotid artery into internal carotid artery and external carotid artery. A fly-through path is determined to automatically move the virtual camera based on the intersecting coordinates of two bisectors on the circumscribed quadrangle of segmented carotid artery. In consideration of the interactive rendering speed and the usability of standard graphic hardware, endoscopic view of carotid artery is generated by using surface rendering algorithm with perspective projection method. In addition, the endoscopic view is provided with ray casting algorithm for off-line navigation of carotid artery. Experiments have been conducted on both mathematical phantom and clinical data sets. This algorithm is more effective than key-framing and topological thinning method in terms of automated features and computing time. This algorithm is also applicable to generate the centerline of renal artery, coronary artery, and airway tree which has tree-like cylinder shape of organ structures in the medical imagery.

Algorithms↗

PubMed1997

The limitations of decision trees and automatic learning in real world medical decision making.

The decision tree approach is one of the most common approaches in automatic learning and decision making. The automatic learning of decision trees and their use usually show very good results in various "theoretical" environments. But in real life it is often impossible to find the desired number of representative training objects for various reasons. The lack of possibilities to measure attribute values, high cost and complexity of such measurements, and unavailability of all attributes at the same time are the typical representatives. For this reason we decided to use the decision trees not for their primary task--the decision making--but for outlining the most important attributes. This was possible by using a well-known property of the decision trees--their knowledge representation, which can be easily understood by humans. In a delicate field of medical decision making, we cannot allow ourselves to make any inaccurate decisions and the "tips," provided by the decision trees, can be of a great assistance. Our main interest was to discover a predisposition to two forms of acidosis: the metabolic acidosis and respiratory acidosis, which can both have serious effects on child's health. We decided to construct different decision trees from a set of training objects. Instead of using a test set for evaluation of a decision tree, we asked medical experts to take a closer look at the generated trees. They examined and evaluated the decision trees branch by branch. Their comments show that trees generated from the available training set mainly have surprisingly good branches, but on the other hand, for some, no medical explanation could be found.

Acidosis↗

PubMedDate not supplied

Automatic segmentation of medical images using image registration: diagnostic and simulation applications.

Automatic identification of the boundaries of significant structure (segmentation) within a medical image is an are of ongoing research. Various approaches have been proposed but only two methods have achieved widespread use: manual delineation of boundaries and segmentation using intensity values. In this paper we describe an approach based on image registration. A reference image is prepared and segmented, by hand or otherwise. A patient image is registered to the reference image and the mapping then applied to ther reference segmentation to map it back to the patient image. In general a high-resolution nonlinear mapping is required to achieve accurate segmentation. This paper describes an algorithm that can efficiently generate such mappings, and outlines the uses of this tool in two relevant applications. An important feature of the approach described in this paper is that the algorithm is independent of the segmentation problem being addresses. All knowledge about the problem at hand is contained in files of reference data. A secondary benefit is that the continuous three-dimensional mapping generated is well suited to the generation of patient-specific numerical models (e.g. finite element meshes) from the library models. Smoothness constraints in the morphing algorithm tend to maintain the geometric quality of the reference mesh.

Algorithms↗

PubMed2004

A (sub)graph isomorphism algorithm for matching large graphs.

We present an algorithm for graph isomorphism and subgraph isomorphism suited for dealing with large graphs. A first version of the algorithm has been presented in a previous paper, where we examined its performance for the isomorphism of small and medium size graphs. The algorithm is improved here to reduce its spatial complexity and to achieve a better performance on large graphs; its features are analyzed in detail with special reference to time and memory requirements. The results of a testing performed on a publicly available database of synthetically generated graphs and on graphs relative to a real application dealing with technical drawings are presented, confirming the effectiveness of the approach, especially when working with large graphs.

Algorithms↗

PubMed2004

Mental imagery for a conversational robot.

To build robots that engage in fluid face-to-face spoken conversations with people, robots must have ways to connect what they say to what they see. A critical aspect of how language connects to vision is that language encodes points of view. The meaning of my left and your left differs due to an implied shift of visual perspective. The connection of language to vision also relies on object permanence. We can talk about things that are not in view. For a robot to participate in situated spoken dialog, it must have the capacity to imagine shifts of perspective, and it must maintain object permanence. We present a set of representations and procedures that enable a robotic manipulator to maintain a "mental model" of its physical environment by coupling active vision to physical simulation. Within this model, "imagined" views can be generated from arbitrary perspectives, providing the basis for situated language comprehension and production. An initial application of mental imagery for spatial language understanding for an interactive robot is described.

Algorithms↗

PubMed2005

Redundant manipulator techniques for partially decentralized path planning and control of a platoon of autonomous vehicles.

An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.

Algorithms↗

PubMedDate not supplied

Efficient volume preserving approach for skeleton-based implicit surfaces.

This paper presents an efficient way to preserve the volume of implicit surfaces generated by skeletons. Recursive subdivision is used to efficiently calculate the volume. The criterion for subdivision is obtained by using the property of density functions and treating different types of skeletons respectively to get accurate minimum and maximum distances from a cube to a skeleton. Compared with the criterion generated by other ways such as using traditional Interval Analysis, Affine Arithmetic, or Lipschitz condition, our approach is much better both in speed and accuracy.

Algorithms↗

PubMed1991

A prospective analysis of inter-rater agreement between a physician and a physician's assistant in selecting QMR vocabulary terms.

We prospectively identified a cohort of 19 hospital inpatients to serve as a test set to determine the agreement between a physician and a physician's assistant in selecting and entering Quick Medical Reference (QMR) vocabulary terms for use in QMR case analysis mode. For positive findings, there was good agreement between data entered by the physician's assistant and data entered by the physician. Overall matches for positive findings were 0.66 concordance for the initial state, and 0.67 for the final state. Concordance for negative findings was substantially lower. The QMR generated differential diagnoses lists of the physician and physician's assistant were judged as similar in 14 (74%) of the 19 cases when QMR critique and assert functions were used.

Artificial Intelligence↗

PubMed1994

Integrating consultation and semi-automatic knowledge acquisition in a prototype-based architecture: experiences with dysmorphic syndromes.

The paper describes an application of cognitive theories of Tversky and Rosch to prototype similarity of dysmorphic syndromes cases. The knowledge-based system supports diagnostic consultation and research in dysmorphic syndromes. It has been used routinely for many years. The knowledge base is semi-automatically generated from known cases of an outpatient clinic. Some results of the evaluation process of the system's achievements are shown. General conclusions based on the experience with this successful system are discussed.

Artificial Intelligence↗

PubMed2005

An automatic warning system for epileptic seizures recorded on intracerebral EEGs.

OBJECTIVE: A new clinical seizure waning system for intracerebral EEG is proposed. It is aimed at a better performance than existing systems and at user tuneability. METHODS: The system employs data filtering in multiple bands, spectral feature extraction, Bayes' theorem, and spatio-temporal analysis. The a priori information in Bayes' theorem was provided by 407 h of EEG from 19 patients having 152 seizures. RESULTS: The testing data (19 patients, 389 h, 100 seizures, independent of the training data) yielded a sensitivity of 89.4%, a false detection rate of 0.22/h, and median delay time of 17.1 s when tuning was used, and 86%, 0.47/h and 16.2 s without tuning. Missed seizures were of short duration or had subtle seizure activity. False detections were caused by technical artefacts, non-epileptic large amplitude rhythmic bursts or very low amplitude activity. It was established that performance could easily be tuned. Results were also compared to the clinical system of . CONCLUSIONS: The system offers a performance that is acceptable for clinical use. User tuneability allows for reduction in false detection with minimal loss to sensitivity. SIGNIFICANCE: Epilepsy monitoring generates large amounts of recordings and requires intense observation. Automatic seizure detection and warning systems reduce review time and facilitate observation. We propose a method with high sensitivity and few false alarms.

Acute Disease↗

PubMed2004

Combination of a naive Bayes classifier with consensus scoring improves enrichment of high-throughput docking results.

We have previously shown that a machine learning technique can improve the enrichment of high-throughput docking (HTD) results. In the previous cases studied, however, the application of a naive Bayes classifier failed to improve enrichment for instances where HTD alone was unable to generate an acceptable enrichment. We present here a protocol to rescue poor docking results a priori using a combination of rank-by-median consensus scoring and naive Bayesian categorization.

Algorithms↗

PubMedDate not supplied

User involvement in the early stages of the development of an aircraft warning system.

There is an increasing awareness of the importance and the benefits to be attained from consulting the end-users during system and product development. Although the rationale of utilizing the expertise of end-users in the system development life cycle appears to provide an apparently straightforward, even 'ideal' approach, there are many difficulties associated with eliciting the required knowledge from experts, both general and specific to every user group. Furthermore, many developers do not know how to involve users, or if they do, they do not utilize them to best effect. In the avionics sphere, the wealth of knowledge possessed by line pilots and flight engineers represents a vital information resource for the design of future flight-deck systems. As a specific example, this paper overviews some of the considerations which arose from working with these end-users in the early stages of the development of a warning and diagnostic system for civil aircraft. The end-goal of this particular phase of the work was the generation of guidelines for the design of the interface for the software engineers to use when building the prototype, and the methodological approach taken to achieve this is reported here.

Aircraft↗

PubMed2005

Spatiotemporal video segmentation based on graphical models.

This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.

Algorithms↗

PubMed2006

Effective palette indexing for image compression using self-organization of Kohonen feature map.

The process of limited-color image compression usually involves color quantization followed by palette re-indexing. Palette re-indexing could improve the compression of color-indexed images, but it is still complicated and consumes extra time. Making use of the topology-preserving property of self-organizing Kohonen feature map, we can generate a fairly good color index table to achieve both high image quality and high compression, without re-indexing. Promising experiment results will be presented.

Algorithms↗

PubMed2006

A model-based approach for estimating human 3D poses in static images.

Estimating human body poses in static images is important for many image understanding applications including semantic content extraction and image database query and retrieval. This problem is challenging due to the presence of clutter in the image, ambiguities in image observation, unknown human image boundary, and high-dimensional state space due to the complex articulated structure of the human body. Human pose estimation can be made more robust by integrating the detection of body components such as face and limbs, with the highly constrained structure of the articulated body. In this paper, a data-driven approach based on Markov chain Monte Carlo (DD-MCMC) is used, where component detection results generate state proposals for 3D pose estimation. To translate these observations into pose hypotheses, we introduce the use of "proposal maps," an efficient way of consolidating the evidence and generating 3D pose candidates during the MCMC search. Experimental results on a set of test images show that the method is able to estimate the human pose in static images of real scenes.

Algorithms↗

PubMed2006

Ant-based clustering and topographic mapping.

Ant-based clustering and sorting is a nature-inspired heuristic first introduced as a model for explaining two types of emergent behavior observed in real ant colonies. More recently, it has been applied in a data-mining context to perform both clustering and topographic mapping. Early work demonstrated some promising characteristics of the heuristic but did not extend to a rigorous investigation of its capabilities. We describe an improved version, called ATTA, incorporating adaptive, heterogeneous ants, a time-dependent transporting activity, and a method (for clustering applications) that transforms the spatial embedding produced by the algorithm into an explicit partitioning. ATTA is then subjected to the most rigorous experimental evaluation of an ant-based clustering and sorting algorithm undertaken to date: we compare its performance with standard techniques for clustering and topographic mapping using a set of analytical evaluation functions and a range of synthetic and real data collections. Our results demonstrate the ability of ant-based clustering and sorting to automatically identify the number of clusters inherent in a data collection, and to produce high quality solutions; indeed, we show that it is particularly robust for clusters of differing sizes and for overlapping clusters. The results obtained for topographic mapping are, however, disappointing. We provide evidence that the solutions generated by the ant algorithm are barely topology-preserving, and we explain in detail why results have--in spite of this--been misinterpreted (much more positively) in previous research.

Algorithms↗

PubMed1990

Time and tiles on the brain.

Both the quasicrystalline appearance of mammalian cerebral cortex and the quasiperiodicity of mammalian cerebral compound field potentials (EEG/ERBP) have long been noted. A recent experiment claims to show the eigenvalue spectrum of a quasiperiodic tiling of coupled oscillators in the plane; and this spectrum of resonant frequencies has some analogies with that of mammalian EEG/ERBP. Concurrently, Connectionist literature now admits the significance of internally generated network rhythmicity in Non-Lipschitzian neurodynamics. It may be time to test the hypotheses of: (a) quasi-crystalline icosahedral symmetry of neocortical architectonics and (b) some fractal characteristics of EEG/ERBP under behavioral conditions.

Animals↗

PubMed1991

An expert system for inferring structures of organic compounds from their mass spectra.

Development of an 'expert system' for elucidation of structures of acyclic organic compounds is described. An expert system is a computer program that embodies some of the heuristic problem-solving knowledge of human experts so that it can effectively be used as an aid to decision making. The expert system described in this paper is intended to assist a chemist in arriving at plausible structures, the input data being the mass spectrum, molecular formula and presence (if known) of functional groups. The program generates chemically possible structures for the given molecular formula and can use, where available, the constraints imposed by the mass spectrum of the compound and by any known functional groups. The program makes use of a new algorithm for obtaining a canonical representation of structures and a new heuristic for incorporating constraints of the mass spectrum. This work constitutes a case study of the application of artificial intelligence techniques in chemistry and the material presented highlights this motivation.

Chemistry, Organic↗