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At least 1,135 records · Page 63Linked to original sources
PubMed1992

The introduction of cystic fibrosis carrier screening into clinical practice: policy considerations.

Routine prenatal testing for cystic fibrosis (CF) should be halted until the detection rate reaches 95 percent. Pilot studies are needed in order to evaluate the feasibility of meeting education, consent, and counseling requirements in order to facilitate informed reproductive decisions by clients and to minimize the potential for confusion, stigmatization, and discrimination. Primary care physicians may not be trained adequately to provide appropriate information, and prenatal visits may not be an ideal setting. The public's interest in carrier testing, prenatal testing, and pregnancy termination is uncertain because CF patients have an increasing median survival, variable disability, and normal intelligence. Even with a goal that limits testing for the purpose of informed reproductive decision making, the considerable cost of screening per case prevented must be considered before it becomes public policy. Until these issues have been clarified, the duty of primary care physicians is to inform patients of the test's availability and to refer interested patients to qualified genetic counselors rather than to provide the test themselves.

Attitude to Health↗
PubMed1997

A temporal database mediator for protocol-based decision support.

To meet the data-processing requirements for protocol-based decision support, a clinical data-management system must be capable of creating high-level summaries of time-oriented patient data, and of retrieving those summaries in a temporally meaningful fashion. We previously described a temporal-abstraction module (RESUME) and a temporal-querying module (Chronus) that can be used together to perform these tasks. These modules had to be coordinated by individual applications, however, to resolve the temporal queries of protocol planners. In this paper, we present a new module that integrates the previous two modules and that provides for their coordination automatically. The new module can be used as a standalone system for retrieving both primitive and abstracted time-oriented data, or can be embedded in a larger computational framework for protocol-based reasoning.

Artificial Intelligence↗
PubMed1992

Stability of the intelligence quotient-language quotient relation: is discrepancy modeling based on a myth?

Diagnostic and service eligibility decisions are often made on the basis of the relation between assessments of cognitive ability and assessments of language ability. A discrepancy between cognitive and language performance, with cognition being higher, is thought to be a positive predictor of ability to benefit from intervention. This triage model assumes reasonable stability of cognitive and language measures over time. We evaluated the stability, over 1- and 2-year periods, of the relation between a cognitive measure and two language measures. We examined whether the cognitive-language relation for these measures changed significantly over time and whether children remained in the same service eligibility category, based on the discrepancy model, over time. Results indicated substantial changes in the cognitive-language relation over time. Children's eligibility for service, based on the discrepancy model, also fluctuated greatly over time. We conclude that a discrepancy model of triage based on broad cognitive and language measures is not an effective means of determining who should receive service. Alternative triage methods were presented.

Child↗
PubMed2005

A parallel decision tree-based method for user authentication based on keystroke patterns.

We propose a Monte Carlo approach to attain sufficient training data, a splitting method to improve effectiveness, and a system composed of parallel decision trees (DTs) to authenticate users based on keystroke patterns. For each user, approximately 19 times as much simulated data was generated to complement the 387 vectors of raw data. The training set, including raw and simulated data, is split into four subsets. For each subset, wavelet transforms are performed to obtain a total of eight training subsets for each user. Eight DTs are thus trained using the eight subsets. A parallel DT is constructed for each user, which contains all eight DTs with a criterion for its output that it authenticates the user if at least three DTs do so; otherwise it rejects the user. Training and testing data were collected from 43 users who typed the exact same string of length 37 nine consecutive times to provide data for training purposes. The users typed the same string at various times over a period from November through December 2002 to provide test data. The average false reject rate was 9.62% and the average false accept rate was 0.88%.

Algorithms↗
PubMed2000

Healthcare applications of knowledge discovery in databases.

Many healthcare leaders find themselves overwhelmed with data, but lack the information they need to make informed decisions. Knowledge discovery in databases (KDD) can help organizations turn their data into information. KDD is the process of finding complex patterns and relationships in data. The tools and techniques of KDD have achieved impressive results in other industries, and healthcare needs to take advantage of advances in this exciting field. Recent advances in the KDD field have brought it from the realm of research institutions and large corporations to many smaller companies. Software and hardware advances enable small organizations to tap the power of KDD using desktop PCs. KDD has been used extensively for fraud detection and focused marketing. There is a wealth of data available within the healthcare industry that would benefit from the application of KDD tools and techniques. Providers and payers have a vast quantity of data (such as, charges and claims), but not effective way to analyze the data to accurately determine relationships and trends. Organizations that take advantage of KDD techniques will find that they offer valuable assistance in the quest to lower healthcare costs while improving healthcare quality.

Artificial Intelligence↗
PubMed2006

Stroke Active Guideline Evaluation (STAGE) project.

In 2005 the American Stroke Association's task force on the development of stroke systems established that providers and policymakers at the local, state and national levels can make significant contributions to reducing the devastating effects of stroke by working to promote coordinated systems that improve patient care. In the last few years in North America and Canada several quality stroke registers have been implemented with the aim of improving the processes of care by the diffusion and implementation of national guidelines and by the identification and correction of critical points of stroke care provided in the hospitals participating in the register. The Italian guidelines for stroke, SPREAD, have been developed with the aim of generating a tool applicable to the Italian clinical setting, able to promote the planning and linking of the assistant interventions between the different phases of the stroke care process, from the hyper-acute to the rehabilitation phase, and from primary to secondary prevention in order to harmonise and streamline the actions of the various health-care providers involved in the different phases of the diagnostic and therapeutic path of patients with stroke. The primary end-point of the Stroke Active Guideline Evaluation (STAGE) project, founded by the Italian Ministry of Health in 2003, is the diffusion, implementation and validation of the Italian Guideline for Stroke, SPREAD, in 15 acute care and 3 rehabilitative institutions across Italy. Secondary end-points are the evaluation of impact of the implementation of a workflow management in the processes of care and the identification of a national, streamlined diagnostic and therapeutic path for ischaemic stroke patients. An existing electronic patient record (EPR) has been shared with the referents of the Centres participating in the study and adapted to SPREAD's indicators. This EPR has been augmented with the decision support system. The STAGE project represents the first Italian effort in this direction. A lot of work has to be done before this goal will be achieved, but as Albert Einstein said "Imagination is more important than intelligence".

Database Management Systems↗
PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗
PubMed2026

Precision periodontology in clinical practice: bridging omics and clinical decision-making.

BACKGROUND: Precision periodontology integrates molecular diagnostics, genomics, and advanced imaging into clinical decision-making. Despite major advances in microbiome characterisation, host genetics, and inflammatory biomarkers, their translation into routine care remains limited. OBJECTIVES: To critically appraise current evidence on microbiome-based profiling, genetic and epigenetic markers, host-response biomarkers, and three-dimensional imaging in periodontology, and to propose a conceptual decision-support framework linking diagnostic outputs to potential therapeutic actions and future implementation research. MATERIALS AND METHODS: A narrative review searching PubMed/MEDLINE, Scopus, Embase, and the Cochrane Library (2010-2025) using terms related to precision periodontology, subgingival microbiome, periodontitis genetics and epigenetics, salivary and GCF biomarkers, aMMP-8, CBCT, risk assessment, and artificial intelligence. Priority was given to meta-analyses, systematic reviews, longitudinal studies, and guideline documents. RESULTS: Microbiological testing has defined but narrow indications; single-SNP genotyping has not demonstrated clinical utility commensurate with cost; aMMP-8 point-of-care testing is among the most extensively investigated host-response tools and may have adjunctive value in selected monitoring and peri-implant scenarios; however, current evidence remains insufficient to support routine diagnostic implementation. CBCT may directly influence surgical decision-making through defect morphology characterisation. AI-based models show promise but lack prospective clinical validation. These conclusions are consistent with the 20th EFP Workshop Consensus Report. CONCLUSIONS: Precision periodontology currently operates in addition to, rather than in replacement of, conventional staging and grading. We propose a conceptual decision-threshold framework for the selective consideration of molecular and advanced imaging tools when their additive contribution may meaningfully inform management. This framework should be regarded as a research-oriented decision-support model rather than a validated clinical algorithm. CLINICAL RELEVANCE: Clinicians are provided with a structured, evidence-based framework that identifies specific clinical scenarios where molecular diagnostics, host-response biomarkers, and three-dimensional imaging may meaningfully modify periodontal treatment decisions, supporting the operationalisation of precision approaches in daily practice.

Humans↗
PubMed1991

The diagnosis of acute abdominal pain with computer assistance: worldwide perspective.

This presentation describes the use of computer aided decision support in acute abdominal pain. The development of such support and the feasability of providing it are described with reference to worldwide studies involving nearly 100,000 patients in the UK, the European Community and worldwide. This presentation will give an overview of the experienced gained in these and other studies. As a result of this experience, it will be suggested: a) The diagnosis of acute abdominal pain by inexperienced emergency surgeons remains a difficult problem. 2) Doctors who have been assisted by a computer have, in many instances, improved their diagnostic and decision-making performance. 3) This improvement has not been due to superior "artificial intelligence" of the computer--but due to the computer acting as an educational focus and a stimulus to good clinical practice. 4) On an international level, these studies have been immensely valuable. They have helped bring together different national groups and helped to develop common medical terminology--as well as foster collaborative "spin-off" in terms of research around the world.

Abdomen, Acute↗
PubMed1992

[Formal decision aids in gastroenterology--results of a survey].

Formal decision aids such as scores, decision-trees and expert systems, are recommended for supporting research and daily clinical work. In the field for gastroenterology it is unknown, to which degree these tools are accepted and applied in clinical routine. We therefore conducted a mail survey in order to find out whether clinical gastroenterologists know, use or want formal decision-aids. To all clinical members of a german gastroenterological scientific society (Deutsche Gesellschaft für Verdauungs- und Stoffwechselkrankheiten, n = 584) an information leaflet and a questionnaire was sent. The form contained questions about use, knowledge and requests with respect to decision-aids in gastroenterology and concerning the attitude to computerized decision-aids in general. 584 clinicians received the questionnaire, 215 sent it back for analysis (39%). Formal decision-aids were used by half of the survey participants (56%), mainly three scores (Child-Pugh, Best and other indices for inflammatory bowel disease, Ranson) and four classifications (TNM, Forrest, Savary-Miller, Paquet). Computer-based formal decision-aids (e.g. expert systems) were used by a minority. Clinicians, who applied formal decision-aids stated more frequently a request for further decision-aids (72%) than those who did not (46%). A considerable part of the survey participants believed that computerized decision-aids will come into clinical routine (52%) and will improve education (37%) and clinical practice (35%). 88% were convinced, that decision-aids should be tested in controlled clinical trials before a clinical use can be recommended. There is a discrepancy between propagation of formal decision-aids and it's clinical use. Only a few scores and classifications are used in clinical routine.(ABSTRACT TRUNCATED AT 250 WORDS)

Artificial Intelligence↗
PubMed1995

Extracting knowledge from large medical databases: an automated approach.

Tools which can uncover patterns in patients' records and then make predictions based on that knowledge are and will continue to be high priority in many medical informatics groups. These tools are impacting the performance of outcome studies by discovering patterns which can then be verified with standard statistical tools. This paper demonstrates INC2.5, a general classification system, as a tool for assisting physicians in the decision making process. INC2.5 gathers information from patient records and builds a decision tree which is used to assist physicians in predicting the outcome of new patients. The decision tree will also reveal any patterns which the system found in the data. Successful results of such a system can be used to enhance outcome studies as well as to spread clinical information to areas with fewer resources.

Algorithms↗
PubMed2003

Pervasive self-care solutions in telecardiology. Typical use cases from the EPI-MEDICS project.

In western countries, heart disease is the main cause of premature death. Most of cardiac deaths occur out of hospital. Because of a continuously growing elderly population, the number of heart attacks is steadily increasing. Symptoms are often interpreted incorrectly. Victims do not survive long enough to benefit from inhospital treatments. To reduce the time before treatment, the only useful diagnostic tool to assess the presence of a cardiac event is the electrocardiogram (ECG). Event and transtelephonic ECG recorders are used to improve decision-making but require setting up new infrastructures. The pervasive solution proposed by the European EPI-MEDICS project is an intelligent Personal ECG Monitor for the early detection of cardiac events. It includes part of the patient electronic health record (EHR), embeds a web server and decision-making techniques, generates different alarm levels and forwards alarm messages to the relevant care providers by means of new generation wireless communication. It is cost saving, involving care providers only if necessary, without requiring to set-up specific infrastructures. Healthcare becomes personalized, wearable and ubiquitous.

Arrhythmias, Cardiac↗
PubMed1982

Validity of a WISC-R short form with male delinquents.

Investigated the validity of the Vocabulary-Block Design short form as an estimate of Full Scale IQ in a clinical population of 100 adjudicated white male delinquents. The mean age was 15.8. The difference between the means of the short form and the full Scale IQ was small and nonsignificant. The correlation between the short form and Full Scale IQ was .82 and accounted for 67% of the variance shared by the measures. The short form was found to classify correctly about two-thirds of the Ss by intelligence category. Similarly, about two-thirds of the Ss matched Vocabulary-Block Design discrepancy direction with Verbal-Performance IQ discrepancy. It was concluded the short form was useful as a screening device, but inadequate for making individual treatment program decisions or identifying potential recidivists.

Adolescent↗
PubMedDate not supplied

Causal reasoning in computer programs for medical diagnosis.

Over the last decade substantial advances have been made in the use of causal pathophysiological knowledge in artificial intelligence-based programs for medical diagnosis. Various forms of causal representations have been used. They include probabilistic models, quantitative models, qualitative models, and models that describe causal relations at multiple levels of detail. This paper briefly analyses these methods using three representative systems. Outstanding problems and possible direction in further exploitation of causal reasoning for medical decision-support systems are also discussed.

Artificial Intelligence↗
PubMed1995

The relationship between intelligence and vigilance in children at risk.

The purpose of this study was to compare two competing models as an explanation of the relationship between intelligence and sustained attention in educationally at-risk kindergarten children. One model assumes that lower-IQ subjects allocate greater amounts of attentional resource of information-processing tasks than higher-IQ subjects, whereas the other model assumes that a "less-than" optimal level of arousal is associated with decrements in task performance across time. Twenty-nine teacher-nominated at-risk and 29 normal achieving kindergarten students were administered the Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R) and vigilance taks. Signal detection measures of stimulus detectability (d'), decision criterion (beta), correct detections, and false alarms were used to assess children's sustained attention across three time periods (2, 4, and 6 min). The important results were (a) high-risk children were inferior on d' measures when compared to normal achieving children, (b) vigilance measures did not vary over time in either group, and (c) intelligence and vigilance shared a common factor in high-risk, but not low-risk, children. The results suggest that children educationally at risk suffer deficits related to attentional capacity for processing information.

Achievement↗
PubMed1969

Coping with novelty.

Explore the source record for details and available documents.

Adaptation, Psychological↗
PubMed2004

Correlates of treatment-related decision-making capacity among middle-aged and older patients with schizophrenia.

BACKGROUND: Antipsychotic medications constitute the backbone of treatment for schizophrenia. Current guidelines require clinicians to obtain patients' informed consent for treatment, but few empirical studies of the capacity of patients with schizophrenia for meaningful consent in this context exist. This issue may be particularly relevant for middle-aged and older patients, as the cognitive changes associated with normal aging may have an adverse impact on decision-making processes. We examined the range, stability, and correlates of treatment-related decisional capacity in this patient population. METHODS: Participants included 59 middle-aged and older patients with schizophrenia or schizoaffective disorder and 38 normal comparison subjects. Baseline measures included the MacArthur Competence Assessment Tool for Treatment (MacCAT-T), psychopathology rating scales, and the Mattis Dementia Rating Scale. Patients also completed a neuropsychological test battery. The MacCAT-T was readministered to patients at a 1-month follow-up. RESULTS: Relative to the comparison subjects, the patients had worse understanding of disclosed material; however, a wide range of performance was observed among patients. Variability in MacCAT-T performance was not predicted by demographic characteristics; there were no significant correlations between psychopathology ratings and MacCAT-T scores. Cognitive test scores were often significant correlates of capacity, particularly in terms of understanding and reasoning. The MacCAT-T scores were stable during the 1-month follow-up. CONCLUSIONS: Overall, middle-aged and older outpatients with schizophrenia had worse understanding of disclosed information than did normal comparison subjects, but such group comparisons obscure remarkable heterogeneity among patients. Differences in capacity appeared more related to cognitive functions than to severity of psychopathology. Such information about barriers to capacity may help in developing more effective methods of providing informed consent.

Aged↗
PubMed2000

Forensic assessment of juvenile delinquents: prevalence of psychopathology and decision-making at court in the netherlands.

Dutch juvenile criminal law, concerning minors between 12 and 18 years old, is marked by its pedagogical character. In cases of serious psychosocial problems or psychiatric disorders, the juvenile court may request a forensic examination in order to be able to impose a measure of restraint. This study was aimed at investigating to what extent the juvenile criminal law achieves the aim enhancing professional help in those cases for which such assistance is indicated. One hundred and eight juveniles who were brought before the court were assessed multidisciplinarily. Sixty-five per cent of the youngsters were qualified for 'definite caseness'. For less than half of them a forensic assessment was ordered by the court. In conclusion, young delinquents should be screened for psychiatric disorders more adequately as soon as they are taken into custody.

Adolescent↗