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PubMed1986

Assessment of the accuracy of regression equations proposed for estimating premorbid intellectual functioning on the Wechsler Adult Intelligence Scale.

This investigation examined the accuracy of regression equations proposed by Wilson et al. (1978) for estimating premorbid intellectual quotients (IQs) on the Wechsler Adult Intelligence Scale (WAIS). Actual Verbal, Performance, and Full Scale IQs in a sample of 69 neurologically normal adults were compared against their estimated premorbid levels. While the equations provided an adequate overall fit to the data, actual IQ values at the extremes of the WAIS Scales were found to be most susceptible to underestimation (high actual IQ values) or overestimation (low actual IQ values). The clinical importance of this finding and possible applications of the equations are discussed.

Adolescent↗
PubMed1992

Effects of major depression on estimates of intelligence.

This study examined whether patients with major depressive disorder manifest deficits in intelligence during affective episodes and following clinical improvement. WAIS-R scores were contrasted in 100 patients in an episode of major depression with 50 normal controls, matched to the patient sample in terms of demographic variables and estimates of premorbid IQ. The groups were equivalent in verbal IQ, but, in line with previous studies, the depressed patients had a pronounced deficit in performance IQ. A patient subsample was administered the WAIS-R under unlimited time conditions to determine whether the time constraints of performance IQ subtests contributed to the magnitude of the verbal-performance IQ discrepancy. This discrepancy was only slightly reduced with untimed scoring. Subgroups of depressed patients were retested with the WAIS-R within one week (n = 26) or two months (n = 33) following treatment with electroconvulsive therapy. In both subsamples, IQ scores were improved at posttreatment testing relative to pretreatment, but with little change in the verbal-performance IQ discrepancy. These and related findings suggested that a performance IQ deficit is characteristic of depressed patients regardless of affective state.

Adult↗
PubMed2006

Measuring the intelligibility of conversational speech in children.

Conversational speech is the most socially-valid context for evaluating speech intelligibility, but it is not routinely examined. This may be because it is difficult to reliably count the number of words in the unintelligible portions of the sample. In this study four different approaches to dealing with this problem are examined. Each is based on the assumption that it is possible to perceive syllables in unintelligible strings even when the target words are unknown; these unintelligible syllables can then be used to estimate the number of unintelligible words in these samples using at least four different approaches. Preliminary data are presented for each of the four approaches based on conversational speech from two convenience samples including 320 children with normal (or normalized) speech and 202 children with speech delay. Differences among the four approaches are discussed.

Case-Control Studies↗
PubMedDate not supplied

The relationship of cortisol to practice-related gains in intelligence among older persons.

Based on data collected from two separate samples of older adults, the present study explored the role of cortisol in mediating practice-related gains in fluid intelligence (Gf) among older adults. Analyses across samples involved treatment group participants who received stress inoculation training in order to reduce anxiety concerning intellectual performance; waiting list control group participants did not receive training until the experiment(s) were completed. Practice effects were examined for both groups. In Study 1, the sample consisted of a heterogeneous (re: concerns about intellectual performance) group of older adults, and Study 2 participants were older adults who self-reported as being at least moderately anxious or concerned about intellectual performance declines. The two samples differed on health (p < .01), with Study 2 participants being healthier (as determined via self-report). Results indicated that practice, but not training, effects were evident for measures of crystallized ability (Gc) and Gf across both studies. The data also suggested that cortisol mediation was different for the two samples in that it was negatively correlated with Gf in the first sample, and, though not significant, positively correlated with Gf in the second. The same directional relationships were evident for the measure of Gc. Comparisons between studies regarding correlations between cortisol and practice-related gains in performance were significant for Gf (p < .01) and approached significance for Gc (p < .07). These data seem to suggest that for some older persons, higher levels of cortisol interfere with the effects of practice on Gf performance, while for others, higher cortisol facilitates such gains in performance.

Aged↗
PubMed2005

Artificial intelligence in hematology.

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Artificial Intelligence↗
PubMed2006

The influence of tonal movement and vowel quality on intelligibility in singing.

This paper investigates the perceptual consequences on vowel intelligibility caused by high-pitched tones. Previous research in speech perception, especially with sung speech, has shown that perceptual difficulties generally increase significantly with rising pitch. The stimuli for the perception experiments under consideration include three tensed German vowels /a, e, i/, produced by a soprano in three different pitches as well as rising contours and falling contours. The participants made use of a response box with three keys labeled /a/, /e/, /i/. On hearing an item, the correct key had to be pressed as fast as possible. The present paper shows that processing time, vowel quality and pitch contour are factors that have to be taken into account.

Adult↗
PubMed2006

The intelligibility of tracheoesophageal speech, with an emphasis on the voiced-voiceless distinction.

Total laryngectomy has far-reaching effects on vocal tract anatomy and physiology. The preferred method for restoring postlaryngectomy oral communication is prosthetic tracheoesophageal (TE) speech, which like laryngeal speech is pulmonary driven. TE speech quality is better than esophageal or electrolarynx speech quality, but still very deviant from laryngeal speech. For a better understanding of neoglottis physiology and for improving rehabilitation results, study of TE speech intelligibility remains important. Methods used were perceptual evaluation, acoustic analyses, and digital high-speed imaging. First results show large variations between speakers and especially difficulty in producing voiced-voiceless distinction. This paper discusses first results of our experiment.

Adult↗
PubMed2005

A genomewide scan for intelligence identifies quantitative trait loci on 2q and 6p.

Between 40% and 80% of the variation in human intelligence (IQ) is attributable to genetic factors. Except for many rare mutations resulting in severe cognitive dysfunction, attempts to identify these factors have not been successful. We report a genomewide linkage scan involving 634 sibling pairs designed to identify chromosomal regions that explain variation in IQ. Model-free multipoint linkage analysis revealed evidence of a significant quantitative-trait locus for performance IQ at 2q24.1-31.1 (LOD score 4.42), which overlaps the 2q21-33 region that has repeatedly shown linkage to autism. A second region revealed suggestive linkage for both full-scale and verbal IQs on 6p25.3-22.3 (LOD score 3.20 for full-scale IQ and 2.33 for verbal IQ), overlapping marginally with the 6p22.3-21.31 region implicated in reading disability and dyslexia.

Adolescent↗
PubMed2005

An intelligent ventilation and oxygenation management system in neonatal intensive care using fuzzy trend template fitting.

This paper describes an open loop feedback intelligent system for neonatal intensive care management. The system provides a tool enabling the user to make the final decision to accept or reject the advice given. The system collects 18 parameters from the bedside monitor and ventilator using a Medical Information Bus (MIB) system. Comparison between the system's recommendations and seven clinical users (three doctors and four nurses) actions was made during monitoring of seven neonates with gestation age of 27-31 weeks for 124.13 h (mu=17.7329, sigma=5.3843 h, range=10.40-23.85 h). The validation process compared the recommendations triggered by the system with the user feedback (agree, disagree, wait). The system made 191 recommendations in total, 33 of which (17%) were for ventilation and 158 (83%) for oxygenation. The clinician agreed with the system ventilation decisions in 30 occasions (91%) and in 148 occasions for the system oxygenation decisions (94%). The overall percentage of the agreement between the system and the clinician was 93%.

Artificial Intelligence↗
PubMed2000

An intelligent diabetes software prototype: predicting blood glucose levels and recommending regimen changes.

Maintaining optimal blood glucose (BG) control is difficult for type 1 diabetes mellitus (T1DM) patients when typical daily regimens of food, insulin and exercise are altered. Artificial intelligence (AI) systems consisting of treatment algorithms calibrated through large datasets of patient specific information may offer a solution. Such a system can predict BG level changes resulting from regimen disturbances and recommend regimen changes for compensation. A software prototype based on neural network, fuzzy logic, and expert system concepts was developed and evaluated to determine feasibility and efficacy of a patient specific prediction model. BG data are the primary driver for adapting existing functions to patient specific prediction algorithms. Mean absolute percent error (MAPE) between actual and predicted BG values from inputs of daily insulin, food, and exercise information for an T1DM test subject was 10.5% using a calibrated model. The prototype is limited by the requirement for a rigid testing schedule, human error and situational circumstances such as alcohol consumption, illness, infection, stress, and significant hormonal imbalances. No significant conclusions regarding model validity can be drawn due to limited evaluation process and subject sample size, although the prototype has demonstrated viability as a learning tool for diabetes patients. Increased impetus for further development of this prototype and similar AI models may materialize when more effective diagnostic and data capture tools become available to reduce testing and improve accuracy of the model with more input data.

Algorithms↗
PubMed2004

Management of insulin therapy in urban diabetes patients is facilitated by use of an intelligent dosing system.

The Intelligent Dosing System (IDS, Dimensional Dosing Systems, Inc., Wexford, PA) is a software suite that incorporates patient-specific, dose-response data in a mathematical model, and then calculates the new dose of agent needed to achieve the next desired therapeutic goal. We evaluated use of the IDS for titrating insulin therapy. The IDS was placed on handheld platforms and provided to practitioners to use in adjusting total daily insulin dose. Fasting glucose, random glucose, and hemoglobin A1c were used as markers against which insulin could be adjusted. Values of markers expected at the next follow-up visit, as predicted by the model, were compared with levels actually observed. For 264 patients, 334 paired visits were analyzed. Average age was 54 years, diabetes' duration was 10 years, and body mass index was 33.2 kg/m(2); 57% were female, 88% were African American, and 92% had type 2 diabetes. The correlation between IDS suggested and actual prescribed total daily dose was high (r = 0.99), suggesting good acceptability of the IDS by practitioners. Significant decreases in fasting glucose, random glucose, and hemoglobin A1c levels were seen (all P < 0.0001). No significant difference between average expected and observed follow-up fasting glucose values was found (145 vs. 149 mg/dL, P = 0.42), and correlation was high (r = 0.79). Mean observed random glucose value at follow-up was comparable to the IDS predicted level (167 vs. 168 mg/dL, P = 0.97), and correlation was high (r = 0.73). Observed follow-up hemoglobin A1c was higher than the value expected (7.9% vs. 7.4%, P < 0.0055), but correlation was good (r = 0.70). These analyses suggest the IDS is a useful adjunct for decisions regarding insulin therapy even when using a variety of markers of glucose control, and can be used by practitioners to assist in attainment of glycemic goals.

Artificial Intelligence↗
PubMed2001

Optical search for extraterrestrial intelligence with Air Cerenkov telescopes.

We propose using large Air Cerenkov telescopes (ACTs) to search for optical, pulsed signals from extraterrestrial intelligence. Such dishes collect tens of photons from a nanosecond-scale pulse of isotropic equivalent power of tens of solar luminosities at a distance of 100 pc. The field of view for giant ACTs can be on the order of 10 square degrees, and they will be able to monitor 10-100 stars simultaneously for nanosecond pulses of about 6th magnitude or brighter. Using the Earth's diameter as a baseline, orbital motion of the planet could be detected by timing the pulse arrivals.

Astronomy↗
PubMed2006

Long-term use of risperidone in children with disruptive behavior disorders and subaverage intelligence: efficacy, safety, and tolerability.

OBJECTIVE: The aim of this study was to assess the long-term efficacy and tolerability of risperidone in the treatment of children and adolescents with disruptive behavior disorder (DBD) and below-average intelligence (IQ < 84) over a cumulative period of 2 years. METHODS: We followed 48 patients (6-15 years of age), who had previously completed a 1- year open-label study of risperidone, for an additional year of treatment. Efficacy was assessed using the conduct problem subscale of the Nisonger Child Behavior Rating Form (N-CBRF) as a primary outcome measure; other N-CBRF subscales, the Aberrant Behavior Checklist (ABC), and the Clinical Global Impression (CGI) of severity were secondary efficacy measures. Safety and tolerability were also assessed. RESULTS: Of the 48 patients enrolled in this extension study, 33 (69%) completed the trial. The efficacy benefits from the original study were maintained over the course of the extension study. Safety and tolerability were good overall, with the number of adverse events (AEs) decreasing in the extension trial, compared to the original trial. Six patients (13%) discontinued owing to AEs. Weight gain observed in the original trial stabilized during this extension trial. Cognitive testing demonstrated small, but significant, improvements in cognitive ability. CONCLUSIONS: Risperidone is safe and effective in treating DBDs in children over a cumulative period of 2 years.

Adolescent↗
PubMed2004

Adaptive user displays for intelligent tutoring software.

Intelligent tutoring software (ITS) holds great promise for K-12 instruction. Yet it is difficult to obtain rich information about users that can be used in realistic educational delivery settings--public school classrooms--in which eye tracking and other user sensing technologies are not suitable. We are pursuing three "cheap and cheerful" strategies to meet this challenge in the context of an ITS for high school math instruction. First, we use detailed representations of student cognitive skills, including tasks to assess individual users' proficiency with abstract reasoning, proficiency with simple math facts and computational skill, and spatial ability. Second, we are using data mining and machine learning algorithms to identify instructional sequences that have been effective with previous students, and to use these patterns to make decisions about current students. Third, we are integrating a simple focus-of-attention tracking system into the software, using inexpensive, web cameras. This coarse-grained information can be used to time the display of multimedia hints, explanations, and examples when the user is actually looking at the screen, and to diagnose causes of problem-solving errors. The ultimate goal is to create non-intrusive software that can adapt the display of instructional information in real time to the user's cognitive strengths, motivation, and attention.

Algorithms↗
PubMed2005

The Intelligent Dosing System: application for insulin therapy and diabetes management.

Diabetes mellitus is an increasing public health problem. Insulin is an essential tool in the management of hyperglycemia, but methods of dose adjustment are purely empirical. The Intelligent Dosing System (IDS, Dimensional Dosing Systems, Inc., Wexford, PA) is a software suite that incorporates patient-specific, dose-response data in a mathematical model and then calculates the new dose of the medication needed to achieve the next desired therapeutic goal. We discuss the application of the IDS in insulin management. The IDS concept and the initial modeling used to construct an insulin doser are reviewed first. Additional data are then provided on the use of the IDS for titrating insulin therapy in a clinical setting. Finally, recent modifications in the IDS software and future applications of this technology for insulin dosing and diabetes management are discussed.

Algorithms↗
PubMed1998

Mapper: an intelligent restriction mapping tool.

MOTIVATION: To determine the most powerful artificial intelligence techniques for automated restriction mapping, and use them to create a powerful multiple-enzyme restriction mapping tool. RESULTS: The most effective search engine utilized model-driven exhaustive search and a form of binary logic pruning based on Pratt's separation theory. Additional experimentation led to the development of an input preprocessing module which significantly speeds up searches, and an output post-processing module which enables users to analyze large solution sets and reduce their apparent complexity. AVAILABILITY: An executable version of the resultant tool, Mapper, can be downloaded from our Web site (http://www.ai.eecs.uic.edu) by selecting the 'Software' option. CONTACT: nelson@eecs.uic.edu (http://www.ai.eecs.uic.edu/ñelson).

Algorithms↗
PubMed1991

Artificial intelligence methods for theory representation and hypothesis formation.

This article describes artificial intelligence methods for representing theories in molecular biology, and for improving the predictive power of these theories using experimental data. A program called GENSIM provides a framework for representing theories that includes descriptions of classes of biological objects (genes, enzymes, etc.), and processes that specify potential interactions among these objects (such as enzymatic reactions). GENSIM can employ a theory specified within this framework to predict the outcomes of biological experiments. A program called HYPGENE comes into play when the observed outcome of an experiment does not match the outcome predicted by GENSIM. HYPGENE works backward from the error in GENSIMs prediction to postulate changes to both the theory embodied by GENSIM, and the presumed initial conditions of the experiment. I view HYPGENEs hypothesis generation task as a design problem, and I have adapted AI methods developed for design and planning to this task. These techniques were developed in conjunction with an in-depth study of the discovery of the gene regulation mechanism of attenuation in the E. coli tryptophan operon. Both GENSIM and HYPGENE have been tested on sample problems from the history of attenuation, and produced many of the same solutions as biologists did.

Artificial Intelligence↗
PubMed2005

Sign language recognition and translation: a multidisciplined approach from the field of artificial intelligence.

In recent years, research has progressed steadily in regard to the use of computers to recognize and render sign language. This paper reviews significant projects in the field beginning with finger-spelling hands such as "Ralph" (robotics), CyberGloves (virtual reality sensors to capture isolated and continuous signs), camera-based projects such as the CopyCat interactive American Sign Language game (computer vision), and sign recognition software (Hidden Markov Modeling and neural network systems). Avatars such as "Tessa" (Text and Sign Support Assistant; three-dimensional imaging) and spoken language to sign language translation systems such as Poland's project entitled "THETOS" (Text into Sign Language Automatic Translator, which operates in Polish; natural language processing) are addressed. The application of this research to education is also explored. The "ICICLE" (Interactive Computer Identification and Correction of Language Errors) project, for example, uses intelligent computer-aided instruction to build a tutorial system for deaf or hard-of-hearing children that analyzes their English writing and makes tailored lessons and recommendations. Finally, the article considers synthesized sign, which is being added to educational material and has the potential to be developed by students themselves.

Artificial Intelligence↗

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