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PubMed1988

Longitudinal validity of the Miller Assessment for Preschoolers: study II.

The classificational accuracy of the Miller Assessment for Preschoolers was examined in relation to intelligence and achievement measures assessed four years later. Specifically, the test's predictive validity was evaluated using the recommended 5% (Refer) and 25% cut-offs (Watch). The results' implications for decision strategies in research on validity for preschool screening instruments are discussed.

Child Development↗
PubMed2006

Information. Mapping the money.

Dr Foster Intelligence aims to improve the use and accessibility of information to offer people more control over their care. It will also provide management with the information required to make effective business decisions. The new service will be 'taking advantage of private-sector expertise for public-sector advantage.

Access to Information↗
PubMed1997

[Systemic counseling in dyssocial behavior, delinquency and violence].

The article summarizes characteristic interactive patterns in social systems concerned with acting-out, delinquent and violent behavior in adolescents. As a consequence, it develops a multi systems consultation approach. Core features of such an approach are the clarification of service demands and of available resources, the development of new and sometimes unusual cooperation, positive connotation of distrust and chaos, and an intelligent questioning of the usefulness of ones owen professional activities. At the end the question is raised, whether and in which ways educators, physicians and psychologists could involve themselves in political decision processes about media, work and welfare legislation, which influence their adolescent clients life situation.

Adolescent↗
PubMed2005

Prediction of pancreatic cancer by serum biomarkers using surface-enhanced laser desorption/ionization-based decision tree classification.

OBJECTIVE: In order to improve the prognosis of pancreatic cancer patients, it is crucial to explore novel tools for its early diagnosis. Here, we attempted to screen serum biomarkers to distinguish pancreatic cancer from non-cancer individuals. METHODS: 47 serum samples from pancreatic cancer patients, 39 of whom had small surgically resectable cancers, were collected before surgery, and an additional 53 serum samples from age- and sex-matched individuals without cancer were used as controls. The surface-enhanced laser desorption/ionization (SELDI) ProteinChip was applied to analyze serum protein profiling. 54 samples (27 with pancreatic cancer and 27 controls) were analyzed in the training set by a decision tree algorithm to be able to separate pancreatic cancer from controls. A double-blind test was used to determine the sensitivity and specificity of the classification model. RESULTS: A panel of six biomarkers was selected to set up a decision tree as the classification model. The model separated effectively pancreatic cancer from control samples, achieving a sensitivity of 88.9% and a specificity of 74.1%. The double-blind test challenged the model with a sensitivity of 80% and a specificity of 84.6%. CONCLUSION: The SELDI ProteinChip combined with an artificial intelligence classification algorithm shows great potential for the diagnosis of pancreatic cancer.

Adult↗
PubMed1979

A study of mental status and anamnestic factors related to the decision for inpatient or outpatient treatment.

Reviewed previous studies of the determinants of disposition decision-making. Experimental flaws in these studies are indicated. A study of the intake decision process and its relationship to mental status and anamnestic variables obtained during the intake examination is presented (N = 523). Results suggest that diagnoses of psychosis and personality disorder are rleated to inpatient care, while the diagnosis of neurosis is related to outpatient care. In addition, depressed/suicidal symptomatology is found to be related to inpatient treatment, while a previous history of either sexual maladjustment or stubbornness/retardation is found to be related to outpatient care. Results are discussed in terms of universal and local criteria that are involved in intake decision-making.

Adult↗
PubMed1993

Metaphor graphics to support integrated decision making with respiratory data.

Support for data integration in the intensive care unit (ICU) often includes efforts to improve the display of data. An electronic version of a flowsheet (table of numbers) with optimal line graphs is by far the most common format in current ICU computer workstation technology, yet there is little evidence that this format provides particularly good support for human integration of data. The present work introduces a new form of graphic representation, one that is far more metaphoric, far more tailored to the intensive care unit than a line graph. This graphic system, called volume rectangles represents mechanical ventilator data in such a way that is easy to keep different types of variables conceptually separated, yet easy to see how they relate in a truly integrated way. Volume rectangles are one example of a general approach to display of data called the metaphor graphic approach, which is being evaluated in this and other contexts. Metaphor graphics are custom tailored visual displays designed to look like the real world situation from which the data is collected but not in a literal sense of 'look like'. Anecdotal observation suggests that such graphics are easy to learn, are remembered over long period, and are good decision support tools when the task is finding patterns in a mass of data.

Artificial Intelligence↗
PubMed1990

Medical expert systems: design and applications in pulmonary medicine.

Expert systems are computer applications with a built-in knowledge of a special field to solve problems like a human expert on this subject. An expert system consists of an inference component for problem specification and solving, a knowledge base for storage of data, facts, rules and heuristics, an interface for knowledge acquisition, another for the interaction with the user, and a component for reasoning. Pulmonary expert systems are used for automatic interpretations of lung function data which are measured on-line and directly computed. There are also some expert systems for consultation in difficult pulmonary cases and for protection against overlooking rare diseases. Perhaps the most successful applications of pulmonary expert systems are for educational purposes and a large variety of teachware is available. Pulmonary expert systems are presently limited to small applications; often it is necessary to type in large amounts of data and to follow a deeply structured cumbersome dialog. Also, the problem of responsibility for computer decisions has to be mentioned. But pulmonary expert systems as integrated supplements of normal pulmonary measuring devices, as decision support, and as parts of pulmonary teachware will be helpful tools for the pneumological physician.

Artificial Intelligence↗
PubMed1990

An epidemiologic approach to computerized medical diagnosis--AEDMI program.

A program called "An Epidemiological Approach to Computerized Medical Diagnosis" (AEDMI) is presented. Using an interactive questionnaire, physician-patient interviews are conducted and a summary of the relevant clinical data is provided. Standard items, obtained on a multi-centre basis, form a large-scale data base. Simultaneously, the reasoning of clinical experts in each real case is analyzed to obtain a knowledge-rules data base. The methodology of the program combines Bayesian systems, expert systems, and other new lines of research such as neural networks or case-based reasoning. The general concepts of clinical decision making aid systems are reviewed. This publication is aimed at obtaining international cooperation.

Artificial Intelligence↗
PubMed2004

Legacy of the American eugenics movement: implications for primary care.

One hundred years ago the first "genetic revolution" promised a boon to society through the rational application of scientific knowledge about heredity. Leading American physicians, psychologists,social workers, scientists, educators, and philanthropists advocated a eugenics agenda that called for the elimination of the "unfit." This legacy has affected profoundly the current nondirective model of genetic counseling. As primary care now prepares for the age of genomic medicine, the history of eugenics provides a perspective for the application of patient-centered care and shared decision-making models to the process of genetic testing.

Eugenics↗
PubMed2003

Searching for discrimination rules in protease proteolytic cleavage activity using genetic programming with a min-max scoring function.

This paper presents an algorithm which is able to extract discriminant rules from oligopeptides for protease proteolytic cleavage activity prediction. The algorithm is developed using genetic programming. Three important components in the algorithm are a min-max scoring function, the reverse Polish notation (RPN) and the use of minimum description length. The min-max scoring function is developed using amino acid similarity matrices for measuring the similarity between an oligopeptide and a rule, which is a complex algebraic equation of amino acids rather than a simple pattern sequence. The Fisher ratio is then calculated on the scoring values using the class label associated with the oligopeptides. The discriminant ability of each rule can therefore be evaluated. The use of RPN makes the evolutionary operations simpler and therefore reduces the computational cost. To prevent overfitting, the concept of minimum description length is used to penalize over-complicated rules. A fitness function is therefore composed of the Fisher ratio and the use of minimum description length for an efficient evolutionary process. In the application to four protease datasets (Trypsin, Factor Xa, Hepatitis C Virus and HIV protease cleavage site prediction), our algorithm is superior to C5, a conventional method for deriving decision trees.

Algorithms↗
PubMed2025

Large Language Model and Knowledge Graph-Driven AJCC Staging of Prostate Cancer Using Pathology Reports.

Background/Objectives: To develop an automated American Joint Committee on Cancer (AJCC) staging system for radical prostatectomy pathology reports using large language model-based information extraction and knowledge graph validation. Methods: Pathology reports from 152 radical prostatectomy patients were used. Five additional parameters (Prostate-specific antigen (PSA) level, metastasis stage (M-stage), extraprostatic extension, seminal vesicle invasion, and perineural invasion) were extracted using GPT-4.1 with zero-shot prompting. A knowledge graph was constructed to model pathological relationships and implement rule-based AJCC staging with consistency validation. Information extraction performance was evaluated using a local open-source large language model (LLM) (Mistral-Small-3.2-24B-Instruct) across 16 parameters. The LLM-extracted information was integrated into the knowledge graph for automated AJCC staging classification and data consistency validation. The developed system was further validated using pathology reports from 88 radical prostatectomy patients in The Cancer Genome Atlas (TCGA) dataset. Results: Information extraction achieved an accuracy of 0.973 and an F1-score of 0.986 on the internal dataset, and 0.938 and 0.968, respectively, on external validation. AJCC staging classification showed macro-averaged F1-scores of 0.930 and 0.833 for the internal and external datasets, respectively. Knowledge graph-based validation detected data inconsistencies in 5 of 150 cases (3.3%). Conclusions: This study demonstrates the feasibility of automated AJCC staging through the integration of large language model information extraction and knowledge graph-based validation. The resulting system enables privacy-protected clinical decision support for cancer staging applications with extensibility to broader oncologic domains.

artificial intelligence↗
PubMedDate not supplied

Using pulmonary function testing in the diagnosis and treatment of asthma.

Asthmatics have remarkable changes in their pulmonary function in response to numerous external stimuli and internal controls. Serial pulmonary function testing in the office, hospital, at home, or the work place allows the objective measurement that is necessary to intelligently diagnose and treat these patients. Once the patient and the physician understand how to use the techniques for monitoring the degree of airways obstruction, they become a key in medical management decisions.

Asthma↗
PubMed2026

National Antimicrobial Resistance Monitoring System: Three Decades of Advancing Public Health Through Integrated Surveillance of Antimicrobial Resistance.

Antimicrobial resistance (AMR) occurs when bacteria and other microorganisms adapt in ways that make medicines less effective, causing infections that are harder to treat and more likely to spread. According to the Centers for Disease Control and Prevention (CDC), AMR infections affect millions of Americans each year and contribute to thousands of deaths (CDC, 2019). After three decades of operation, the U.S. National Antimicrobial Resistance Monitoring System (NARMS) stands as a model of sustained, collaborative public health surveillance. What began in 1996 as an effort to track resistance in Salmonella and E. coli O157 has evolved into a One Health surveillance network monitoring AMR across the farm-to-fork continuum. Through a partnership among CDC, the Food and Drug Administration (FDA), the U.S. Department of Agriculture (USDA), state and local health departments, and universities, NARMS has become the backbone of foodborne AMR surveillance in the United States. The past decade has been particularly transformative. NARMS explored new sampling to include companion animals, minor livestock, aquaculture, surface water, and wildlife. Whole-genome sequencing (WGS) revolutionized the program's capabilities, enabling timely identification of emerging pathogens and revealing how resistance genes spread. Near real-time public dashboards make NARMS data accessible to researchers, clinicians, regulators, and policymakers. NARMS data shape decisions about new animal drug approvals, guide stewardship programs, and inform clinical treatment guidelines nationwide. As NARMS enters its fourth decade with a 2026-2030 strategic plan, the program will leverage artificial intelligence and metagenomics while expanding surveillance to fill remaining gaps ensuring this vital system continues to protect the food supply and both human and animal health from AMR.

Antimicrobial Resistance (AMR)↗
PubMed2003

Emerging information management technologies and the future of disease management.

Disease management (DM) has become a widely accepted way to support care delivery in the chronically ill patient population. Patients enrolled in these programs have been shown to have better health, fewer complications and comorbidities, and lower health care costs. The development of advanced information management technologies is further enhancing the role DM plays in optimizing outcomes and cost-effectiveness in clinical care. These emerging information management technologies (EIMT) include advances in software, hardware, and networking, all of which share common impact attributes in their ability to improve cost-effectiveness of care, quality of care, and access to care. Specific examples include interactive websites with the ability to engage patients in the self-care management process, the embedding of biometric devices (digital scales, modem-enabled glucose meters in the home, blood pressure monitoring, etc.), workflow and care coordination programs that add intelligence via guideline-directed alerts and reminders to the delivery process, registries that include a summary of personal health data that can be used as a reference point for improved clinical decisions, and the systematic collection of aggregated, de-identified clinical, administrative, and cost data into comprehensive data sets to which predictive modeling analytic tools can be applied. By way of case example, we also present data from a controlled clinical trial utilizing EIMT in the form of home-based weight measurement using a digital scale and linkage to a care coordination center for the management of severe congestive heart failure. Outcome results on 85,515 patient-months of an aggregate commercial and Medicare continuously enrolled population demonstrated an average reduction of care utilization (hospitalization) of 57% and a reduction in related delivery cost (per member per year payments) of 55%. We conclude that EIMT have already begun to offer significant and quantifiable benefits to DM and are likely to become heavily embedded in care management strategies in the future.

Aged↗
PubMed2002

Biological data integration: wrapping data and tools.

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web as well as data generated by software. We present an approach to wrapping web data sources, databases, flat files, or data generated by tools through a database view mechanism. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, second builds the expected output with respect to the virtual structure. Our wrappers are composed of a retrieval component based on an intermediate object view mechanism called search views mapping the source capabilities to attributes, and an eXtensible Markup Language (XML) engine, respectively, to perform these two tasks. The originality of the approach consists of: 1) a generic view mechanism to access seamlessly data sources with limited capabilities and 2) the ability to wrap data sources as well as the useful specific tools they may provide. Our approach has been developed and demonstrated as part of the multidatabase system supporting queries via uniform object protocol model (OPM) interfaces.

Algorithms↗
PubMed2006

Accentuate the negative: the positive effects of negative acknowledgment.

Three studies investigated the capacity of negative acknowledgment, the admission of an unfavorable quality, to elicit relatively positive responses. In Study 1, an acknowledgment that a written paragraph was confusing led individuals to rate the paragraph as clearer than they did when no acknowledgment was offered. In Study 2, a foreign speaker was rated as possessing a clearer voice when he acknowledged his strong accent than when he did not. In Study 3, a hypothetical college applicant's acknowledgment of receiving less than stellar high school grades resulted in a more positive evaluation of those grades. The interpersonal risks and benefits of negative acknowledgment as an impression-management strategy are discussed.

Adolescent↗
PubMed1999

Sterilisation of incompetent mentally handicapped persons: a model for decision making.

Doctors are regularly confronted with requests for sterilisation of mentally handicapped people who cannot give consent for themselves. They ought to act in a medical vacuum because there doesn't exist a consensus about a model for decision making on this matter. In this article a model for decision making is proposed, based on a review of the literature and our own research data. We have attempted to select and classify certain factors which could enable us to arrive at an ethically justifiable method of making a medical decision. In doing so we distinguish two major criteria: heredity and parenting competence, and six minor criteria: conception risk, IQ, age, personality, medical aspects and prognosis and finally support and guidance for the mentally handicapped person. The major criteria give rise to a "situation of necessity". In this situation the physician is confronted with a conflict of values and interests. The minor criteria are of an entirely different ethical order. They can only be considered once the major criteria have created a "situation of necessity". Ultimately it comes down to deciding whether the benefits of sterilisation outweigh the drawbacks and whether the means are appropriate to the end, where efficient contraception is the end and irreversible sterilisation is the means.

Adolescent↗
PubMed1992

[Paced addition. A neuropsychological test for assessment of divided attention].

The Pasat (Paced auditory serial addition task) is a test requiring addition of simple digits presented auditorily in several series of a successively higher pace of presentation. The task reflects the capacity for divided attention, is a measure of information processing speed and has appeared to be sensitive to minor attention deficits. We made a Dutch version characterized by longer time intervals between digits, for use in a study among (altogether 130) middle-aged and elderly persons. This modified version was evaluated with respect to feasibility. It appeared to be fairly feasible, provided sufficient opportunity for practice is given. Two series with inter-stimulus intervals of 4 and 3 seconds respectively were then evaluated with respect to validity and reliability in subjects of 48 to 74 years. Both Pasat series correlated well with two tests of attention: Digit Symbol (WAIS) and d2-test (r = 0.53-0.67), the relation with reaction decision speed being generally weak (r = 0.29-0.33) and weak to absent with a number of memory tests (r = -0.04-0.29). The Pasat performance shows a positive relationship with educational level and intelligence (inter-stimulus interval 4 seconds: r = 0.28 and 0.33 resp.; inter-stimulus interval 3 seconds: r = 0.40, 0.57 resp.). The stability of test performance over a period of about two months is moderate (r = 0.54, 0.61 resp.). In view of the excellent inter-observer reliability (r = 0.99) and the good parallel-test reliability (r = 0.79, 0.68 resp.), this might be explained by fluctuations in the capacity measured, rather than measurement error.(ABSTRACT TRUNCATED AT 250 WORDS)

Aged↗