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At least 1,477 records · Page 82Linked to original sources
PubMed2006

Intelligent semantic interoperability: Integrating knowledge, terminology and information models to support stroke care.

INTRODUCTION: Electronic patient record (EPR) systems for the continuity of care for stroke patient are under development. These systems are based on standards such as for clinical practice, vocabularies, and the HL7 information model. PROBLEM STATEMENT: In order to achieve intelligent semantic interoperability, knowledge about evidence based patient care, vocabulary and information models need to be integrated. METHODOLOGY: A format was developed in which the clinical knowledge, clinical terminology, and standard information models are integrated as specification for the technical implementation of electronic health systems and electronic messages. This format is verified by clinicians and technicians. RESULTS: The document structure consists of meta-information such as version control and changes, purpose of the clinical content, evidence from the literature, variables and values, terminology used, guidelines for application and interpretation, HL7 message models, coding, and technical data specification. Further, XML message excerpts, archetypes and screen designs are developed from these documents to facilitate implementation. CONCLUSION: The combination of these aspects in one document creates valuable content for intelligent semantic interoperability by means of development of messages and systems.

Continuity of Patient Care↗
PubMed1987

Artificial intelligence--its use in nephrology.

Artificial intelligence techniques and expert systems are graduating from research laboratories to enter many human domains of activities. However, initial expectations of the seventies have been transformed with time to a more sober reality. Starting from examples in nephrology, this paper tries to give a balanced view of this new technology. Justification, indication and limitation of present expert systems are discussed as regards their possible goals. The respective roles of the experts and knowledge engineers are described. The need to integrate the artificial intelligence approach into present patient database management systems in order to build up expert database systems is evaluated.

Database Management Systems↗
PubMedDate not supplied

Influence of high pass filtering on the intelligibility of amplitude-compressed speech.

Monosyllabic triplet word intelligibility scores were obtained from normal-hearing and hearing-impaired, loudness-recruiting subjects under two experimental conditions: (1) high-pass (1200 Hz)-filtered, linear amplification, and (2) high-pass (1200 Hz)-filtered, compression amplification using input-to-output ratios of 5:1 and 20:1. Test materials were administered at increased sensation levels of 0, 10, 20, and 30 dB. In general, speech intelligibility was slightly enhanced for normal and hearing-impaired listeners, but only at lower sensation levels. Moreover, the improvement was observed only under the filtered, compression amplification condition for both groups. No important differences were observed between the two compression ratios used. This compression advantage may or may not be observed in clinical hearing aid evaluations.

Adolescent↗
PubMedDate not supplied

The intelligibility of whitened and peak clipped speech.

Consonant-nucleus-consonant monosyllabic words were filltered such that each spectral component had equal energy (i.e., "whitened") and peak clipped in one of four ways: minimal, 20, 30, and 40 dB of clipping. In addition, unmodified consonant-nucleus-consonant words were used as stimuli. These different types of sppech were presented to 20 persons with normal hearing at various sensation levels. The results indicate that whitening and peak clipping do not substantially degrade speech intelligibility. In fact, under some conditions whitening and peak clipping may slightly enhance intelligibility.

Adult↗
PubMed1982

Frequency selectivity and speech intelligibility in noise.

Poor speech intelligibility in noise is a major problem for persons afflicted by a sensorineural hearing loss, and this problem is generally not alleviated by a hearing aid. For a typical hearing loss the effective signal-to-noise ratio is degraded by 10 - 15 dB, predominantly due to impoverished frequency selectivity. The critical ratio averaged over speech frequencies is a convenient measure of this component of the auditory handicap. An attempt to improve speech intelligibility in noise through dichotic combfiltering was not successful.

Audiometry, Pure-Tone↗
PubMed1993

Intelligent processing of loosely structured documents as a strategy for organizing electronic health care records.

Loosely structured documents can capture more relevant information about medical events than is possible using today's popular databases. In order to realize the full potential of this increased information content, techniques will be required that go beyond the static mapping of stored data into a single, rigid data model. Through intelligent processing, loosely structured documents can become a rich source of detailed data about actual events that can support the wide variety of applications needed to run a health-care organization, document medical care or conduct research. Abstraction and indirection are the means by which dynamic data models and intelligent processing are introduced into database systems. A system designed around loosely structured documents can evolve gracefully while preserving the integrity of the stored data. The ability to identify and locate the information contained within documents offers new opportunities to exchange data that can replace more rigid standards of data interchange.

Database Management Systems↗
PubMed1995

An intelligent safety feature for AGV's economic operations: a simulation analysis.

A typical automated guided vehicle (AGV) is equipped with a number of warning and safety devices to prevent injury-causing accidents due to its mishap operations. Standard safety devices, such as an emergency bumper and a non-contact obstacle sensor, sometimes result in uneconomic operations of AGVs since they frequently cause stop-and-go situations. This paper discusses the use of a new intelligent safety feature which not only provides effective warning for the AGV's approach but also helps reduce stop-and-go situations which normally occurred when a sensor detects an obstacle. The proposed feature integrates functional operations of sensors, warning devices, an onboard microprocessor, and the AGV's driving mechanism. Computer simulations of AGV's operations both with and without this intelligent safety feature were also performed and their results are compared.

Computer Simulation↗
PubMed1996

An intelligent learning environment for advanced cardiac life support.

Resuscitation from clinical cardiac arrest is complex and often takes several years to learn. This paper describes an intelligent simulation-based tutor for ACLS which increases students' opportunity to practice before, during and after the ACLS course, thus bridging the gap between studying theory and didactic textbook material and working with patients. Sophisticated reasoning about student performance, compared to an expert model, distinguishes this system from other computerized instruction systems. Intelligence in the tutor allows the system to make the simulation dynamically adaptive to focus on areas where the student's learning needs are greatest. A formative evaluation with two classes of fourth year medical students suggested that the tutor was helpful, realistic and effective. Positive reactions and strong student involvement with the simulation suggest that this simulation-based tutor may improve learning and retention while decreasing anxiety for most students.

Computer Simulation↗
PubMed1997

[An overview on research and application of intelligent materials in modern medicine].

The research on intelligent materials is a new advanced technology, which is much interested by many scientists and engineers in recent years. Some research results have been achieved and used in aeronautics, mecahanics, civil engineering, medicine and other associated fields. In this paper, we present the properties, functions and status of intelligent materials in modern medicine.

Biomedical Engineering↗
PubMed2026

Emerging multidimensional biomarker system for cardiovascular-kidney-metabolic syndrome: from multi-omics integration to clinical artificial intelligence.

Cardiovascular-kidney-metabolic (CKM) syndrome is an emerging clinical entity that highlights the complex, bidirectional interplay among cardiovascular disease, chronic kidney disease, and metabolic disorders, representing a substantial and growing global health burden. This conceptualization marks a paradigm shift from viewing these conditions in isolation to understanding them as an interconnected disease continuum. Traditional biomarkers face significant limitations in the early detection, risk stratification, and precise management of CKM, necessitating a transition towards an integrated framework that captures its multisystem nature. This review systematically outlines an emerging multidimensional biomarker system encompassing key pathological axes such as metabolism, immuno-inflammation, oxidative stress, and biological aging, offering refined risk assessment beyond conventional metrics. The development of this system is propelled by revolutionary platforms, including accessible sampling techniques (e.g., dried blood spots), advanced in vitro models (e.g., multi-organ-on-a-chip), and multi-omics technologies. These platforms not only facilitate a deeper dissection of the heterogeneous origins and inter-organ crosstalk in CKM but also accelerate the discovery and validation of novel biomarkers. Concurrently, artificial intelligence serves as a pivotal tool for clinical translation, effectively integrating high-dimensional data to transform complex molecular profiles into actionable clinical insights. By enabling the construction of dynamic risk prediction and decision-support systems, this review charts a pathway toward proactive, individualized, and precise prevention and management of CKM syndrome.

Humans↗
PubMed1998

An investigation into the relationship between interests and intelligence.

This article relates the six General Occupational Themes (GOTs) and the 23 Basic Interest Scales (BISs) yielded by the Strong Interest Inventory (SII) to age, gender, and performance on the KAIT. The sample included 936 males and females aged 16 to 65 years. MANOVAs and MANCOVAs (covarying education) were conducted, followed by univariate ANOVAs and ANCOVAs. IQ level on KAIT was significantly related to the Investigative and Realistic themes and to numerous interest scales, most notably Writing, Nature, Teaching, Mathematics, and Art. The discrepancy between fluid and crystallized intelligence on the KAIT related significantly to a few variables, but relationships were generally small in magnitude. Significant relationships with age were few; gender related significantly to most variables, consistent with previous research. These findings were interpreted in the context of previous research on the Strong, and on the integration of interests and intellect.

Adolescent↗
PubMed2000

Intelligence: success and fitness.

This chapter presents the consensus among psychometricians regarding the construct of general intelligence ('g') and its measurement. More than any other construct, g illustrates the scientific power of construct validation research. To date, g is carried by more assessment vehicles and saturates more aspects of life than any other dimension of human variation uncovered by psychological science. Phenomena most vital to the core of g's nomological network are reviewed (e.g. abstract learning, information processing, and dealing with novelty). This is followed by coverage of relevant but more peripheral phenomena (e.g. crime, health risk behaviour, and income). Because g constitutes such a ubiquitous aspect of the human condition, its omission in social science research often results in underdetermined causal modelling. Frequently, this constitutes a longstanding error in inductive logic, namely, the Fallacy of the Neglected Aspect. Attending to Carnap's Total Evidence Rule can help to forestall neglected aspects in scientific reasoning.

Child↗
PubMed1976

Ethnicity, socioeconomic status, and pattern of WISC scores as variables that affect psychologists' estimates of "effective intelligence".

Psychologists estimated "true IQs" or "effective intelligence" from WISC profiles that varied for ethnicity (black, Mexican-American, or white), social class (lower or middle), profile (three scatter patterns), and direction of Verbal-Performance Scale discrepancy. Psychologists gave higher IQ estimates to black and Mexican-American children's profiles than to the same profiles of white children. Social class was not a significant factor. Profiles with much scatter received higher IQs than profiles with limited scatter. The pattern of subtest scores also affected estimates, while the direction of the Verbal-Performance discrepancy was not significant. Finally, the WISC was judged to be more valid for white than for black and Mexican-American children. Explanations of the findings were discussed.

Black or African American↗
PubMed2026

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We included 309 slides from 96 GAS cases collected at Peking University Third Hospital from January 2018 to January 2025, representing the largest GAS cohort reported to date for AI research. In addition, we incorporated other morphologically analogous diseases, encompassing a total of 1,320 slides sourced from four categories: normal cervical mucosa (NORM), benign endocervical lesion entities (BELE), HPV-associated adenocarcinoma (HPVA), and endometrioid carcinoma with mucinous differentiation (ECMD). We developed GASPath, based on a novel multiple instance learning framework that efficiently captures fine-grained morphological variations from H&E-stained images. Beyond internal validation, GASPath was evaluated across 12 independent retrospective cohorts and further subjected to large-scale real-world validation on more than 7,000 samples from March 2024 to April 2025. Across three stages, GASPath demonstrated high performance. In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997). In external validation (Stage II), the sensitivity reached 0.902 and improved to 0.968 with proposed strategies. For biopsy samples, GASPath achieved an ROC-AUC of 0.990 (95% CI 0.984-0.997). In large-scale real-world deployment (Stage III, n = 7,056), GASPath achieved a balanced accuracy of 0.953, with 100% sensitivity for GAS (45/45 cases correctly identified). The heatmaps highlight morphological features of GAS that are easily underestimated, such as irregular, angulated glands, subtle loss of nuclear polarity, and mild cytologic atypia, which show substantial morphological overlap with other diagnostic categories. GASPath enables high-sensitivity detection of GAS in routine H&E-stained slides, obviating the need for extensive auxiliary testing while preventing underdiagnosis and misdiagnosis. This advancement addresses a critical gap by streamlining diagnostic workflows without compromising accuracy. Its implementation could enable cost-effective, scalable AI-assisted diagnostics, potentially transforming the early detection and management of this aggressive cancer subtype.

Female↗
PubMed1990

Psychometric intelligence after infantile hydrocephalus. A critical review and reinterpretation.

Methodological issues in research concerning intellectual sequelae of infantile hydrocephalus are reviewed, and a multivariate statistical approach to this problem is proposed and exemplified. The significance of a variety of medical history variables with regard to psychometric intelligence was assessed in a sample of 5- to 8-year-old children who had been shunted in the 1st year of life. Stepwise discriminant analyses revealed that many medical history variables were neutral with regard to intellectual outcome (as assessed by performance on psychometric tests). The presence of additional medical problems in infancy, as well as current ocular defects, were the most significant variables that were associated with a high likelihood of mental retardation. Implications for further research are discussed.

Cerebrospinal Fluid Shunts↗
PubMed1977

Intelligence level of patients with the Duchenne type of progressive muscular dystrophy (pmd-d).

The I.Q. of 129 patients with PMD-D and 27 patients suffering from Werdnig-Hoffmann disease were estimated. Among the patients with PMD-D there was one group without any complicating factors and 3 other groups with additional factors that might influence the intelligence level. Comparing mean values and distribution of I.Q. for all these groups, one can conclude that, besides additional unfavourable pathological and environmental factors in all cases, PMD-D itself causes a small decrease of the I.Q. by about 1 SD. The frequent changes of the EEG record in these patients could reflect involvement of the CNS by the pathological process.

Adolescent↗