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PubMed2002

[Telemedicine: chances and risks].

PROBLEM: Due to the rapid progress in the fields of information technology and data networks, telemedicine applications are growing in number. Besides curative telemedicine, the electronic exchange of medical data and the integration of health information systems between health care providers is gaining importance. Through the improved accessibility of electronic patient record information, considerable risks arise. METHODS: A project for the interconnection of medical picture archiving and communication systems (PACS) between several hospitals is presented and the possibilities for further developing such networking systems utilizing new software technologies for transparent data access between different locations (GRID) and for decision support (software agents) are considered. RESULTS: The availability of the electronic patient record via the data network and the perspective of semi intelligent software systems automatically preparing the data bears great potential for a boost in treatment quality and efficiency. Systems for unique electronic patient identification and for secure digital signature are a prerequisite, but per se not enough to ensure the protection of data against illegitimate access. CONCLUSION: Despite quality and efficiency benefits, challenges in the protection of sensible data and in the change of the physicians role result.

Artificial Intelligence↗
PubMed2006

Potential impact of advanced clinical information technology on cancer care in 2015.

New clinical information technologies now sporadically available will soon be in routine clinical use, bringing many changes to all phases of the cancer care continuum. For example, new technologies such as: (1) The next generation Internet; (2) Real-time clinical decision support systems; (3) Off-line, population-based systems; (4) Large, integrated, individual patient-level phenotypic and genotypic databases with intelligent data mining capabilities; (5) Wireless, invasive and non-invasive physiologic monitoring devices; (6) Natural Language Processing (NLP) systems; and (7) Mathematical models of complex biological systems all have the potential to impact significantly the provision of cancer care throughout its continuum. While new information management and communication techniques and technologies will reduce many of the inefficiencies and inaccuracies of our present systems, there will be an equal, and potentially far more dangerous, set of unintended consequences. Informatics investigators, cancer specialists, and health system administrators must focus on the study of what is working and what is not, as well as, on development and testing of the new clinical information management and communication technologies, if we are to be ready for the future.

Cancer Care Facilities↗
PubMed2004

An intelligent service-based network architecture for wearable robots.

We are developing a novel robot concept called the wearable robot. Wearable robots are mobile information devices capable of supporting remote communication and intelligent interaction between networked entities. In this paper, we explore the possible functions of such a robotic network and will present a distributed network architecture based on service components. In order to support the interaction and communication between the components in the wearable robot system, we have developed an intelligent network architecture. This service-based architecture involves three major mechanisms. The first mechanism involves the use of a task coordinator service such that the execution of the services can be managed using a priority queue. The second mechanism enables the system to automatically push the required service proxy to the client intelligently based on certain system-related conditions. In the third mechanism, we allow the system to automatically deliver services based on contextual information. Using a fuzzy-logic-based decision making system, the matching service can determine whether the service should be automatically delivered utilizing the information provided by the service, client, lookup service, and context sensors. An application scenario has been implemented to demonstrate the feasibility of this distributed service-based robot architecture. The architecture is implemented as extensions to the Jini network model.

Algorithms↗
PubMed1982

Assessing the predictive validity of developmental milestones.

Parental report of development milestones influences the physician's decision to refer for developmental evaluation and early education. The predictive validity of commonly reported milestones was evaluated by collecting data from records in a comprehensive care clinic. Multivariate analyses determined the relationships among age of milestone achievement and Wechsler intelligence Scale for Children-Revised (WISC-R) intelligence quotient (IQ) scores. Other routinely collected medical and demographic information was then added, and stepwise regressions determined the best combinations of predictors of WISC-R IQ scores. Milestones alone predicted 24 to 42% of the variance in WISC-R IQ scores, suggesting that there are meaningful relationships between the age of attainment of milestones and later intellectual functioning. However, when other medical and demographic information was added to the prediction equation, the predictive power of milestones was overshadowed by that of the new variables. Milestones are validated as one criterion for referral for specialized early development services, but adding other objective data, including standardized developmental screening, is recommended for optimal decision making.

Adolescent↗
PubMed2004

Impaired performance in a test of decision-making by opiate-dependent tobacco smokers.

This study tested whether opiate dependence, tobacco smoking, or their combination accompanied impaired performance on the gambling task (GT), which tests decision-making. GT previously detected impairments in patients with lesions of the ventromedial prefrontal cortex and in substance abusers. Four groups were matched on demographic characteristics and intelligence: methadone-maintained smokers (n = 9) and nonsmokers (n = 9), and control (i.e., not opiate-dependent) smokers (n = 9) and nonsmokers (n = 10). The Wisconsin Card Sorting Task (WCST) was administered to test whether differences in GT performance reflected generalized deficits in prefrontal cortical function. While there were no significant group differences on the WCST, groups differed significantly on GT performance (F(3,31) = 2.95, P = 0.048), controlling for depressive symptom ratings and childhood attention deficit hyperactivity disorder. Methadone-maintained smokers (but not nonsmokers) performed more poorly than either of the two control groups (P = 0.007 versus smokers; P = 0.024 versus nonsmokers). In a planned analysis of methadone-maintained subjects, smokers scored more poorly on GT than nonsmokers (F(1,18) = 5.64, P = 0.032) and had more treatment failures (67% heroin use during the last 30 days versus 20%). The findings suggest that among opiate-dependent individuals, tobacco smoking may be a marker for a more severe form of substance abuse disorder, reflecting impaired decision-making, as modeled by GT.

Adult↗
PubMed1988

Spontaneous subarachnoid haemorrhage: expert system for appraisal of the prognosis and computer-supported decision for therapy.

An expert system is presented which allows appraisal of the prognosis and a computer-supported decision for the therapy of patients with acute spontaneous subarachnoid haemorrhage (SAH). The knowledge of physicians as a synthesis of their own and other clinicians' experience is simulated with methods of artificial intelligence by setting up two data banks. In one data bank, selected information on the correlation between initial clinical parameters, on the one hand, and mortality, outcome and complications, on the other, from about 250 neurological publications is stored, taking into consideration the therapeutic regimens applied. A second data bank receives clinical and laboratory data profiles of a patient population which has already been treated. The expert system is able to compare the individual initial findings with the corresponding parameter combination stored in the data banks regarding the decision for therapy of a patient to be treated. This enables both calculation of the probable complications and prediction of the expected outcome in relation to various possible forms of therapy. The expert system can thus indicate the kind of therapy where the lowest number of complications and the best outcome can be expected, thus supporting the decision of the physician. As each new patient is treated, the volume of stored information increases, so the system possesses self-learning characteristics. To check the validity of the prognoses, the outcome estimated by the expert system for 51 patients with spontaneous SAH was compared with the actual outcome, and a high level of agreement was attained.

Decision Making, Computer-Assisted↗
PubMedDate not supplied

Analytic and heuristic processing influences on adolescent reasoning and decision-making.

The normative/descriptive gap is the discrepancy between actual reasoning and traditional standards for reasoning. The relationship between age and the normative/descriptive gap was examined by presenting adolescents with a battery of reasoning and decision-making tasks. Middle adolescents (N = 76) performed closer to normative ideals than early adolescents (N = 66), although the normative/descriptive gap was large for both groups. Correlational analyses revealed that (1) normative responses correlated positively with each other, (2) nonnormative responses were positively interrelated, and (3) normative and nonnormative responses were largely independent. Factor analyses suggested that performance was based on two processing systems. The "analytic" system operates on "decontextualized" task representations and underlies conscious, computational reasoning. The "heuristic" system operates on "contextualized," content-laden representations and produces "cognitively cheap" responses that sometimes conflict with traditional norms. Analytic processing was more clearly linked to age and to intelligence than heuristic processing. Implications for cognitive development, the competence/performance issue, and rationality are discussed.

Adolescent↗
PubMed1978

Intercorrelations among tests of general mental ability and achievement for black and white deaf children.

The purpose of this study was to compare the relative effectiveness of two measures commonly used to predict school achievement of black and white deaf children. The Wechsler Intelligence Scale for Children-Revised and the Hiskey-Nebraska Test of Learning Aptitude correlated significantly with Stanford Achievement Test scores for 23 black children but not for 36 white. Even though the groups differed significantly in WISC-R Performance IQ, Hiskey learning quotient, and in CA, they did not differ in achievement level. While the WISC-R and Hiskey appear to have some predictive validity for the black sample, the findings of no differences in achievement suggest little practical validity of these measures for grouping or placement or for making administrative or instructional decisions.

Achievement↗
PubMed1997

IDIS-KS: an intelligent drug information system as a knowledge server.

Expert System technology in combination with other technologies such as Networks and Data Base systems can prove to be a valuable tool for medical experts, providing decision support and information services, and therefore facilitating and improving their everyday tasks. IDIS-KS described in this paper, is an consultation and information system dedicated to deliver drug information and suggestions about possible treatments to medical practitioners in the National area of Greece.

Computer Communication Networks↗
PubMed2026

Big data in multiple sclerosis.

PURPOSE OF REVIEW: This review summarizes recent key advancements in multiple sclerosis (MS) achieved through the utilization of big data from diverse sources and advanced analytical techniques. RECENT FINDINGS: Real-world evidence (RWE) derived from MS big data has significantly enhanced treatment strategies, redefined the concept of disease progression, refined prognostic models, and facilitated personalized medicine. RWE has highlighted the long-term benefits of early intensive treatment compared to escalation strategies, the unfavorable risk profile associated with treatment de-escalation and the importance of managing treatments during pregnancy. Additionally, it has revealed similarities and differences in the effectiveness and safety of specific high-efficacy therapies, as well as key predictors for switching treatments. RWE has also emphasized the central role of progression independent of relapse activity as a significant driver of disability and predictor of unfavorable long-term outcomes in both adult and pediatric onset MS. A data-driven approach utilizing artificial intelligence and big data has established a comprehensive framework for understanding the disease's evolution. Multimodal big data frameworks - encompassing clinical data, MRI, genomics, biomarkers, and app-based metrics - have demonstrated their ability to enhance diagnostic performance and risk stratification in MS. SUMMARY: Big data approaches are transforming MS research and clinical practice by providing stronger RWE to guide therapeutic decision-making, refining models of disease progression, and developing more precise prognostic tools.

Humans↗
PubMed1977

A comparison of the Stanford-Binet abbreviated and complete forms for developmentally disabled children.

Three abbreviated versions of the Stanford-Binet were reviewed and compared for 50 children with developmental disabilities. The children ranged in age from 6 years - 0 months to 15 years - 11 months. While the IQs obtained from the abbreviated forms correlated highly with the complete Binet IQ, it was felt that the 2-item test yielded too many "misses" both in terms of IQ and classification to be of significant value for use with developmentally disabled children. Although the Terman and Merrill 4-item and Wright versions both yielded considerable "misses" in classification, they were believed to be of definite value to the time-harried examiner. Caution was advised, however, in the use of abbreviated-form IQs as a basis for important diagnostic decisions.

Adolescent↗
PubMed1991

[Medical expert systems and clinical needs].

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Artificial Intelligence↗
PubMed2006

Decision-making in obesity: a study using the Gambling Task.

The present study addresses the issue of whether a "decision-making disorder" could account for the behavioral problems of severely obese patients (BMI score >34) who are not classified by traditional psychiatric Eating Disorder tests. The neuropsychological test employed, the Gambling Task (GT), is not directly related to the food domain, but it is sensitive to failure in making long-term advantageous choices. A comparison was made of 20 obese subjects (OS) and 20 normal-weight subjects (NWS) matched in age, education and IQ. The subjects' personalities and food behavior were assessed from psychological questionnaires, and then the Gambling Task was administered. The number of "good" choices made by the two groups during GT performance differed significantly, and the OS did not learn to maximize advantageous choices like the NWS did. OS behavior could be consistent with a prefrontal cortex defect that implies difficulties in inhibition of excessive food intake.

Adult↗
PubMed1999

PACS workstation respecification: display, data flow, system integration, and environmental issues, derived from analysis of the Conquest Hospital pre-DICOM PACS experience.

This paper is based on 4 years of practical experience with a developmental pre- Digital Imaging and Communications in Medicine (DICOM) picture archiving and communication system (PACS) plus analysis from the respecification study data for a DICOM/HTML PACS replacement. High-performance, but economic, workstations are required within PACS for radiologists to rapidly and accurately report images. For economic reasons such workstations should utilise standard landscape orientation monitors. They must have full Radiology Information System (RIS) integrated reporting functionality to optimise radiologists' work. The workstations must also be capable of displaying request data and both new and associated old images and image reports from multiple modalities. All images should be imported as "folders" according to semi-intelligent "knowledge table" based DICOM 3.0 standard Worklist control exerted by image management servers. This information can be obtained by relevant image lists and decision charts. A description of an optimal standard monitor workstation environment and related issues based on experience and literature review is given.

Data Display↗
PubMed2004

Modafinil improves cognition and response inhibition in adult attention-deficit/hyperactivity disorder.

BACKGROUND: Modafinil, a novel cognitive enhancer, has a clinical profile similar to conventional stimulants such as methylphenidate, despite a seemingly different mechanism of action. Modafinil selectively improves neuropsychological task performance in healthy volunteers, possibly through improved inhibitory control. We examined whether modafinil induced similar improvements in adults with attention-deficit/hyperactivity disorder. METHODS: Twenty patients with a DSM-IV diagnosis of attention-deficit/hyperactivity disorder were entered into a double-blind, randomized, placebo-controlled crossover study using a single 200 mg dose of modafinil. RESULTS: Modafinil produced a similar pattern of cognitive enhancement to that observed in healthy adults, with improvements on tests of short-term memory span, visual memory, spatial planning, and stop-signal motor inhibition. On several measures, increased accuracy was accompanied by slowed response latency. This alteration in the speed-accuracy trade-off may indicate that modafinil increases the ability to "reflect" on problems coupled with decreased impulsive responding. Improvements were also seen in sustained attention, which was unaffected in healthy subjects. CONCLUSIONS: If these benefits are shown to be maintained with chronic administration, modafinil may have potential as an important therapy for attention-deficit/hyperactivity disorder with a similar effect to stimulants such as methylphenidate in improving stop-signal response inhibition but without the side effects commonly experienced with amphetamine-like drugs.

Adult↗
PubMed2001

Artificial intelligence applications in the intensive care unit.

OBJECTIVE: To review the history and current applications of artificial intelligence in the intensive care unit. DATA SOURCES: The MEDLINE database, bibliographies of selected articles, and current texts on the subject. STUDY SELECTION: The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. DATA EXTRACTION: All literature relevant to the topic was reviewed. DATA SYNTHESIS: Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. CONCLUSIONS: The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

Algorithms↗
PubMed1995

When home caregiving ends: a longitudinal study of outcomes for caregivers of relatives with dementia.

OBJECTIVES: To study caregivers' decisions to end home care for relatives with dementia; to study the changes in caregiver functioning over time. DESIGN: A prospective longitudinal follow-up study. SETTING: Individual homes and chronic care facilities in Montreal. PARTICIPANTS: 157 caregiver-dependent dyads, followed up 2 years later; dependents had been diagnosed as having progressive dementia. MEASUREMENTS: A standard interview and a series of standardized psychological questionnaires were given to caregivers, assessing their functioning and their appraisals of the dependent person in their care. Dependents received the Mini-Mental State Examination. MAIN RESULTS: Caregivers cited patient deterioration as the most common reason for ending home care. Most caregivers did not prepare their relative before institutionalization. Most caregivers were satisfied with having ended home care and believed the decision was positive for themselves and their dependent, but a sizable minority of caregivers and dependents had difficulty adjusting to the end of home care. Repeated measures multivariate analyses indicated that caregivers who had discontinued home care because of placement or death of the dependent had improved functioning and quality of life and better health than caregivers still providing home care. CONCLUSIONS: Caregivers most frequently cite deteriorating patient conditions as the main causes of ending home care. Caregiver exhaustion is the single most frequently given reason. Caregivers who were still providing home care at the end of the study were functioning less well than caregivers who had ended home care, despite having initially functioned at better levels.

Aged↗