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At least 1,027 records · Page 57Linked to original sources
PubMed2003

MeKE: discovering the functions of gene products from biomedical literature via sentence alignment.

MOTIVATION: Research on roles of gene products in cells is accumulating and changing rapidly, but most of the results are still reported in text form and are not directly accessible by computers. To expedite the progress of functional bioinformatics, it is, therefore, important to efficiently process large amounts of biomedical literature and transform the knowledge extracted into a structured format usable by biologists and medical researchers. Our aim was to develop an intelligent text-mining system that will extract from biomedical documents knowledge about the functions of gene products and thus facilitate computing with function. RESULTS: We have developed an ontology-based text-mining system to efficiently extract from biomedical literature knowledge about the functions of gene products. We also propose methods of sentence alignment and sentence classification to discover the functions of gene products discussed in digital texts. AVAILABILITY: http://ismp.csie.ncku.edu.tw/~yuhc/meke/

Biomedical Research↗
PubMed2002

Neuro-epileptic determinants of autism spectrum disorders in tuberous sclerosis complex.

Tuberous sclerosis is one of the few established medical causes of autism spectrum disorder and is a unique neurogenetic model for testing theories about the brain basis of the syndrome. We conducted a retrospective case study of the neuro-epileptic risk factors predisposing to autism spectrum disorder in individuals with tuberous sclerosis to test current neurobiological theories of autism spectrum disorder. We found that an autism spectrum disorder diagnosis was associated with the presence of cortical tubers in the temporal but not other lobes of the brain. Indeed, the presence of tubers in the temporal lobes appeared to be a necessary but not sufficient risk factor for the development of an autism spectrum disorder. However, contrary to the predictions of some theories, the location of tubers in specific regions of the temporal lobe, such as the superior temporal gyrus or the right temporal lobe, did not determine which individuals with temporal lobe tubers developed an autism spectrum disorder. Instead, outcome was associated with various indices of epileptic activity including evidence of temporal lobe epileptiform discharges on EEG, the age to onset of seizures in the first 3 years of life and a history of infantile spasms. The results indicated that individuals with tuberous sclerosis are at very high risk of developing an autism spectrum disorder when temporal lobe tubers are present and associated with temporal lobe epileptiform discharges and early-onset, persistent spasm-like seizures. These risk markers constitute useful clinical indicators of prognosis, but further research is required to identify the neurobiological mechanisms responsible for their association with outcome. Most especially, it will be important to test whether, as the findings suggest, there is a critical early stage of brain maturation during which temporal lobe epilepsy perturbs the development of brain systems that underpin 'social intelligence' and possibly other cognitive skills, thereby inducing an autism spectrum disorder.

Autistic Disorder↗
PubMed1984

Mood changes during the internship.

A prospective study using two standardized psychological tests, the Profile of Mood States (POMS) and the Self-Rating Depression Scale (SDS), was conducted in an effort to quantify the emotional changes experienced by internal medicine house staff members during the internship. In contrast to instruments used in previous investigations of this type, the POMS and the SDS are standardized tests with proven reliability and validity. The six mood factors measured, "tension-anxiety," "depression-dejection," "anger-hostility," "vigor-activity," "fatigue-inertia," and "confusion-bewilderment," are reported to be among those factors most often affected by the internship experience. Twenty-three interns completed both tests at four-month intervals during one academic year. One-way analysis of variance for repeated measures revealed that the level of only anger-hostility of the mood factors changed significantly during the year. The intensity of this factor increased between the first and third testing periods before dropping at the end of the year. In contrast to findings in previous studies, the depression and fatigue factors did not increase during the year. By characterizing interns' reactions to the stresses of postgraduate medical education, standardized psychological tests can contribute to improved understanding of these reactions and to more intelligent planning of support systems.

Anger↗
PubMed2001

Comparison of artificial intelligence techniques with UKTRISS for estimating probability of survival after trauma. UK Trauma and Injury Severity Score.

BACKGROUND: The development of TRISS was principally a search for variables that correlated with outcome. It is not known, however, if linear statistical models provide optimal results. Artificial intelligence techniques can answer this question and also determine the most important predictor variables. METHODS: An artificial neural network, using 16 anatomic and physiologic predictor variables, was compared with the latest United Kingdom version of TRISS model. RESULTS: Both methods were 89.6% correct, but TRISS was significantly better by the area under the receiver operating characteristic curve (0.941 vs. 0.921, p < 0.001). The artificial neural network, however, was better calibrated to the test data (Hosmer-Lemeshow statistic, 58.3 vs. 105.4). Head injury, age, and chest injury were the most important predictors by linear or nonlinear methods, whereas respiration rate, heart rate, and systolic blood pressure were underused. CONCLUSION: Prediction using linear statistics is adequate but not optimal. Only half the predictors have important predictive value, fewer still when using linear classification. The strongest predictors swamp any nonlinearity observed in other variables.

Artificial Intelligence↗
PubMed2006

Fast IIR isotropic 2-D complex Gabor filters with boundary initialization.

Gabor filters are widely applied in image analysis and computer vision applications. This paper describes a fast algorithm for isotropic complex Gabor filtering that outperforms existing implementations. The main computational improvement arises from the decomposition of Gabor filtering into more efficient Gaussian filtering and sinusoidal modulations. Appropriate filter initial conditions are derived to avoid boundary transients, without requiring explicit image border extension. Our proposal reduces up to 39% the number of required operations with respect to state-of-the-art approaches. A full C++ implementation of the method is publicly available.

Algorithms↗
PubMed2005

Markerless real-time 3-D target region tracking by motion backprojection from projection images.

Accurate and fast localization of a predefined target region inside the patient is an important component of many image-guided therapy procedures. This problem is commonly solved by registration of intraoperative 2-D projection images to 3-D preoperative images. If the patient is not fixed during the intervention, the 2-D image acquisition is repeated several times during the procedure, and the registration problem can be cast instead as a 3-D tracking problem. To solve the 3-D problem, we propose in this paper to apply 2-D region tracking to first recover the components of the transformation that are in-plane to the projections. The 2-D motion estimates of all projections are backprojected into 3-D space, where they are then combined into a consistent estimate of the 3-D motion. We compare this method to intensity-based 2-D to 3-D registration and a combination of 2-D motion backprojection followed by a 2-D to 3-D registration stage. Using clinical data with a fiducial marker-based gold-standard transformation, we show that our method is capable of accurately tracking vertebral targets in 3-D from 2-D motion measured in X-ray projection images. Using a standard tracking algorithm (hyperplane tracking), tracking is achieved at video frame rates but fails relatively often (32% of all frames tracked with target registration error (TRE) better than 1.2 mm, 82% of all frames tracked with TRE better than 2.4 mm). With intensity-based 2-D to 2-D image registration using normalized mutual information (NMI) and pattern intensity (PI), accuracy and robustness are substantially improved. NMI tracked 82% of all frames in our data with TRE better than 1.2 mm and 96% of all frames with TRE better than 2.4 mm. This comes at the cost of a reduced frame rate, 1.7 s average processing time per frame and projection device. Results using PI were slightly more accurate, but required on average 5.4 s time per frame. These results are still substantially faster than 2-D to 3-D registration. We conclude that motion backprojection from 2-D motion tracking is an accurate and efficient method for tracking 3-D target motion, but tracking 2-D motion accurately and robustly remains a challenge.

Algorithms↗
PubMed2006

A sequential dynamic heteroassociative memory for multistep pattern recognition and one-to-many association.

Bidirectional associative memories (BAMs) have been widely used for auto and heteroassociative learning. However, few research efforts have addressed the issue of multistep vector pattern recognition. We propose a model that can perform multi step pattern recognition without the need for a special learning algorithm, and with the capacity to learn more than two pattern series in the training set. The model can also learn pattern series of different lengths and, contrarily to previous models, the stimuli can be composed of gray-level images. The paper also shows that by adding an extra autoassociative layer, the model can accomplish one-to-many association, a task that was exclusive to feedforward networks with context units and error backpropagation learning.

Algorithms↗
PubMed1983

Limbic lobe epilepsy with paranoid symptoms: analysis of clinical features and psychological tests.

Ten cases of limbic epilepsy with paranoid symptoms were compared with 10 cases of limbic epilepsy without paranoid symptoms and 10 cases of primary generalized epilepsy ( GTC ). The clinical features (onset of seizures, their duration, combination with GTC , seizure control, social adaptability and laterality of foci) and psychological tests (WAIS, Bender-Gestalt, MPI, Y-G, Rorschach) were analyzed. Paranoid epileptics showed poor social adaptation in spite of the seizures being better controlled. They had a low performance IQ, a low object assembly test and a low picture completion test in WAIS. They were less extroversive in MPI, less aggressive and more introversive in the Yatabe -Gilford test. In the Rorschach test, they had a high color response and a form response but the form level was low.

Adult↗
PubMed1994

Low birthweight: a 10-year outcome study of the continuum of reproductive casualty.

Disability rates among low-birthweight infants, particularly those related to congenital abnormality and cerebral palsy, are high. Both prenatal and perinatal factors are likely to be involved in the aetiology of most types of disability. IQ tends to be lower among low-birthweight infants, but does not appear to be closely related to birthweight alone. The confounding effect of social class should be considered when assessing aetiology and outcome. The long-term outcome for the increasing number of low-birthweight infants who survive and receive intensive neonatal care requires to be continually assessed; however, studies should not be confined to the very- and extremely-low-birthweight infant requiring prolonged intensive care, but should include abortions, stillbirths and neonatal deaths. As disability in survivors can relate to preterm birth but not perinatal complications, all low-birthweight infants require to be studied if selective bias is to be solved.

Case-Control Studies↗