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At least 1,531 records · Page 85Linked to original sources
PubMed2006

Humans can adopt optimal discounting strategy under real-time constraints.

Critical to our many daily choices between larger delayed rewards, and smaller more immediate rewards, are the shape and the steepness of the function that discounts rewards with time. Although research in artificial intelligence favors exponential discounting in uncertain environments, studies with humans and animals have consistently shown hyperbolic discounting. We investigated how humans perform in a reward decision task with temporal constraints, in which each choice affects the time remaining for later trials, and in which the delays vary at each trial. We demonstrated that most of our subjects adopted exponential discounting in this experiment. Further, we confirmed analytically that exponential discounting, with a decay rate comparable to that used by our subjects, maximized the total reward gain in our task. Our results suggest that the particular shape and steepness of temporal discounting is determined by the task that the subject is facing, and question the notion of hyperbolic reward discounting as a universal principle.

Adaptation, Physiological↗
PubMed2026

Cyclin-dependent kinase 4 and 6 inhibitors and the breast cancer immune ecosystem: immune remodeling, resistance, and therapeutic reprogramming.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6 inhibitors) combined with endocrine therapy have become a therapeutic backbone for hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer, yet durable disease control is frequently limited by intrinsic and acquired resistance. Canonical tumor-cell mechanisms, including retinoblastoma-pathway escape, cyclin E-cyclin-dependent kinase 2 (CDK2) activation, endocrine adaptation, and phosphoinositide 3-kinase (PI3K)-AKT-mechanistic target of rapamycin (mTOR) signaling, explain only part of this failure because they do not fully capture dynamic immune and stromal remodeling. Preclinical and translational studies indicate that early CDK4/6 inhibition can enhance antigen presentation, activate interferon-related programs, restrain regulatory T cells, and promote a T-cell-inflamed state. These effects are conditional and may not persist during prolonged treatment. Sustained therapy can instead drive heterogeneous resistant niches characterized by stromal remodeling, myeloid recruitment, checkpoint adaptation, and T-cell dysfunction. This immune-state dependence provides a rationale for immune checkpoint blockade, although clinical combinations have shown mixed efficacy and clinically relevant hepatic, pulmonary, and hematologic toxicities. Sequential or lead-in strategies therefore warrant prospective evaluation. Oxidative phosphorylation (OXPHOS) and redox adaptation may sustain selected resistant states and expose context-dependent ferroptotic vulnerabilities. Ferroptosis may connect tumor-cell killing with immune regulation, whereas nanomedicine may improve tumor-selective delivery. Both strategies remain largely preclinical and require further evaluation of pharmacokinetics, biodistribution, toxicity, manufacturability, and immune-cell safety. This Review distinguishes intrinsic from acquired resistance across interpatient, intratumoral, spatial, and temporal dimensions. It integrates tumor-cell escape with cytokine, immune, stromal, vascular, and metabolic remodeling and summarizes emerging therapeutic strategies. We further propose a candidate biomarker-informed framework that integrates genomic profiling, spatial immune architecture, circulating biomarkers, T-cell receptor (TCR) dynamics, transcriptomic and single-cell analyses, artificial intelligence (AI)-assisted multimodal integration, and longitudinal sampling. This framework is intended to support biomarker development and prospective trial design rather than current clinical decision-making, providing a translational basis for testing state-informed and sequence-aware therapeutic strategies.

Humans↗
PubMedDate not supplied

Measuring service line competitive position. A systematic methodology for hospitals.

To mount a broad effort aimed at improving their competitive position for some service or group of services, hospitals have begun to pursue product line management techniques. A few hospitals have even reorganized completely under the product line framework. The benefits include focusing accountability for operations and results, facilitating coordination between departments and functions, stimulating market segmentation, and promoting rigorous examination of new and existing programs. As part of its strategic planning process, a suburban Baltimore hospital developed a product line management methodology with six basic steps: (1) define the service lines (which they did by grouping all existing diagnosis-related groups into 35 service lines), (2) determine the contribution of each service line to total inpatient volume, (3) determine trends in service line volumes (by comparing data over time), (4) derive a useful comparison group (competing hospitals or groups of hospitals with comparable size, scope of services, payer mix, and financial status), (5) review multiple time frames, and (6) summarize the long- and short-term performance of the hospital's service lines to focus further analysis. This type of systematic and disciplined analysis can become part of a permanent strategic intelligence program. When hospitals have such a program in place, their market research, planning, budgeting, and operations will be tied together in a true management decision support system.

Catholicism↗
PubMed1975

[Socio-psychological aspects in marriages of alcoholic women].

In a controlled study during two years we have collected psychological and sociological data on partners of chronic female alcoholics by making use of a semistandardized interview (80 items were evaluated by program Dial and the input scales of Spitzer and his decision logic), of the Freiburger-Persönlichkeits-Inventar (FPI) and of the Hawie-Dahl-test, a German abbreviated version of the Wechsler-Bellevue-Intelligence-test. Furthermore we investigated the interpersonal perception in the marriage of the female alcoholic by a semantic differential. The relatively small number of subjects and controls emphasizes the considerable problems as far to the methodial implications of such a study. Therefore we have to interpretate cautiously our results. We may plead for the hypothese, that the husband of the chronic female alcoholic already from the beginning of the marriage had fifficulties in the realisation of his male role and beyond this that the partnership of the chronic female alchoholic is evidently disturbed by distortion of the interpersonal perception. Finally the interpretation of our results is disucssed with regard to the special approach of examination.

Alcoholism↗
PubMed1976

Inspection time and measured intelligence.

Ten subjects with WAIS Full Scale IQ scores ranging from 119 to 47 were required to discriminate between two lines of markedly different length, exposed in random order for ten different durations, by pressing one of two keys. Estimates of inspection time gamma, the rate at which sensory input is accumulated and passed to subsequent decision processes, were calculated directly from the psychometric functions obtained gamma was found to correlate negatively with subtests contributing to Performance IQ. There was a substantial degree of consistency between estimates of gamma on two different occasions and training did not appear to affect the index, although differences between the two estimates increased as the value of the first estimate increased. Mean overall response latency did not correlate significantly with intelligence and measures obtained from retarded subjects were very like those reported in similar experimental situations utilizing normal subjects. This unexpected finding is interpreted as suggesting that, in this situation, retarded subjects have been prepared to respond on the basis of less evidence than is usually required by intellectually normal subjects.

Adolescent↗
PubMed1998

Distributed cognition and knowledge-based controlled medical terminologies.

Controlled medical terminologies (CMTs) are playing central roles in clinical information systems and medical knowledge resource applications. As these terminologies grow, they are able to support more complex tasks but require more intensive efforts to create and maintain them. Several terminologies are evolving into knowledge bases of medical concepts. The knowledge they include is being used to support distributed cognition in two forms: complex medical decisions involving multiple people and applications, and coordination of maintenance of the terminologies themselves.

Artificial Intelligence↗
PubMed1998

Chaos and complexity--the future for health care HRM.

The need to understand chaos and complexity in organisations has particular importance for health which is bedevilled by the complexity of organisations and the sometimes chaotic nature of its core activities. This article seeks to explore these issues in the context of one of the key functions which is expected to hold together this diversity: Human Resource Management (HRM). An exploration of the nature of HRM in health care as it has evolved indicates that in order for it to have a pivotal role for the future it will need to rethink this role in the changing paradigm which is now emerging; in so doing it could develop as the organisational intelligence for health care in the future facilitating organisational learning and creativity.

Creativity↗
PubMed2005

A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts.

Tacit knowledge of health-care experts is an important source of experiential know-how, yet due to various operational and technical reasons, such health-care knowledge is not entirely harnessed and put into professional practice. Emerging knowledge-management (KM) solutions suggest strategies to acquire the seemingly intractable and nonarticulated tacit knowledge of health-care experts. This paper presents a KM methodology, together with its computational implementation, to 1) acquire the tacit knowledge possessed by health-care experts; 2) represent the acquired tacit health-care knowledge in a computational formalism--i.e., clinical scenarios--that allows the reuse of stored knowledge to acquire tacit knowledge; and 3) crystallize the acquired tacit knowledge so that it is validated for health-care decision-support and medical education systems.

Artificial Intelligence↗
PubMed2005

Convenient intelligent cursor control web systems for Internet users with severe motor-impairments.

The objective of this research work is to simplify and improve the efficiency of cursor control and its interactions on the computer screen by applying fuzzy logic in its decision-making to make Internet users with disabilities use the networked computers conveniently and easily. "Point and click" interactions are one of the key features of operating systems based of graphical user interfaces (GUIs) [C.E. Steriadis, P. Constantinou, Designing human-computer interfaces for quadriplegic people, ACM Trans. Comput.-Hum.-Interact. (TOCHI) 10 (2) (2003) 87-118.]. People with severe motor-impairments due to spinal cord injury (SCI) or spinal cord dysfunction (SCD), however, often have difficulty with accurate and efficient control of pointing devices, limiting their integration to society and unassisted control over their environment through the use of such operating systems [S. Keates, F. Hwang, P. Langdon, P.J. Clarkson, P. Robinson, Cursor measures for motion-impaired computer users, in: Proceedings of ACM SIGCAPH Conference of Assistive Technologies - ASSETS 2002, pp. 135-142.]. The questions "How can someone with severe motor-impairments perform 'point and click' interactions as accurately and efficiently as an able-bodied person?" and "How can these interactions be advanced through use of Computational Intelligence (CI)?" are the driving forces behind the research described in this paper. Through this research, a novel fuzzy mouse cursor control system (FMCCS) is described. The FMCCS core consists of several fuzzy control functions, which define different user interactions with the system. Design and descriptions of these functions, as well first prototype implementation and testing with real users sustaining severe disabilities are presented.

Computer Systems↗
PubMed1982

Competency to consent to research: a psychiatric overview.

The requirement that a subject be competent as a condition of valid consent to participate in research has been accepted by most students of legal and ethical problems of human experimentation. "Competency," however, has lacked a clear and generally agreed on standard. There are four commonly used standards for competency: evidencing a choice in regard to research participation, factual understanding of the issues, rational manipulation of information, and appreciation of the nature of the situation. These standards can be arranged hierarchically such that each represents a stricter test of competency. The decision as to how rigorous a standard for competency is desirable cannot be made on psychiatric grounds. It requires consideration of the policy goals on hopes to attain. Empirical research helps demonstrate the consequences of choosing a particular standard but cannot replace the need for achieving consensus on policy goals.

Beneficence↗
PubMed1999

Telemedicine: the new must for surgery.

The vision of telesurgery comprises a multitude of new communicative elements influencing the way surgeons will treat their patients in the future. The first prerequisite for effective telecommunication is to digitize surgical data. Many medical imaging modalities provide primarily digital data sets, and digital image communication is already entering clinical practice under the labels of teleradiology and telepathology. However, for any surgical purpose, images must refer to tissues. Three-dimensional image reconstruction is warranted, and if such data shall be useful during surgery, different image sources must be combined into some virtual, multiparametric body model and matched to an intraoperatively distorted organ contour. A multitude of detail problems arise, beginning with image standards, data interfaces, data transport, image fusion, registering, contour matching, and, once the data are integrated, all the aspects of surgery-suitable data display and interaction. We refer here to several demonstration projects illustrating such a complex surgical data set and its interactive telecommunication. In all instances, telecommunication was to enable a concentration of distributed medical intelligence at the site where the patient was treated. With further technological development, such telesurgical applications will have a growing influence on patient management and surgical decision making. In the very near future, computer-aided navigation and robotic assistance, based on the same surgical data sets, will be available to all fields of surgery. How decisive the role these methods will play for specific procedures or diseases needs to be determined.

Computer Simulation↗
PubMed1989

The premenstrual syndrome--diagnosis and management.

Premenstrual syndrome is an extremely common disorder. Prospective documentation of symptoms and their temporal relationship to menstruation establishes the diagnosis of PMS. Because the pathophysiologic mechanisms causing PMS are still undetermined, therapy for PMS is largely empiric. A number of pharmacologic agents may be used to reduce PMS symptomatology, and therapeutic decisions should be tailored to the individual's symptom complex. Many women will be able to lead more productive lives if PMS is properly diagnosed and intelligently treated.

Clinical Trials as Topic↗
PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗
PubMed2001

A new concept toward computer-aided medical diagnosis--a prototype implementation addressing pulmonary diseases.

The original concept that led to the structuring of a computer-based medical decision support system (DSS) that is able to support a physician's diagnosis is introduced in this paper. The concept's implementation modeled a generic DSS, the core of which are an integrated knowledge/information base (KIB) along with the inference properties of a data evaluator. The KIB encapsulates the necessary medical knowledge and experience in the form of rules and constraints, preemptive tasks, and actual patients' clinical data. The data evaluator handles approved medical subjective and objective criteria for assessing the KIB's data. The data evaluator incorporates a medical standard data gathering and decision process, structured upon the principles of the clinical differential diagnosis methodology and has been integrated in the system by means of both algorithmic and artificial intelligence techniques. The novel model and the resulted computer-based package have been extensively tested under the Pulmonary Department, University Regional Hospital Patras, Patras, Greece.

Artificial Intelligence↗
PubMed2004

A similarity learning approach to content-based image retrieval: application to digital mammography.

In this paper, we describe an approach to content-based retrieval of medical images from a database, and provide a preliminary demonstration of our approach as applied to retrieval of digital mammograms. Content-based image retrieval (CBIR) refers to the retrieval of images from a database using information derived from the images themselves, rather than solely from accompanying text indices. In the medical-imaging context, the ultimate aim of CBIR is to provide radiologists with a diagnostic aid in the form of a display of relevant past cases, along with proven pathology and other suitable information. CBIR may also be useful as a training tool for medical students and residents. The goal of information retrieval is to recall from a database information that is relevant to the user's query. The most challenging aspect of CBIR is the definition of relevance (similarity), which is used to guide the retrieval machine. In this paper, we pursue a new approach, in which similarity is learned from training examples provided by human observers. Specifically, we explore the use of neural networks and support vector machines to predict the user's notion of similarity. Within this framework we propose using a hierarchal learning approach, which consists of a cascade of a binary classifier and a regression module to optimize retrieval effectiveness and efficiency. We also explore how to incorporate online human interaction to achieve relevance feedback in this learning framework. Our experiments are based on a database consisting of 76 mammograms, all of which contain clustered microcalcifications (MCs). Our goal is to retrieve mammogram images containing similar MC clusters to that in a query. The performance of the retrieval system is evaluated using precision-recall curves computed using a cross-validation procedure. Our experimental results demonstrate that: 1) the learning framework can accurately predict the perceptual similarity reported by human observers, thereby serving as a basis for CBIR; 2) the learning-based framework can significantly outperform a simple distance-based similarity metric; 3) the use of the hierarchical two-stage network can improve retrieval performance; and 4) relevance feedback can be effectively incorporated into this learning framework to achieve improvement in retrieval precision based on online interaction with users; and 5) the retrieved images by the network can have predicting value for the disease condition of the query.

Algorithms↗
PubMed1997

Neural networks in neurotologic expert systems.

Artificial intelligence donates new possibilities to neurotologic research. Neural networks are a computer-based reasoning method which can be applied in expert systems created for clinical decision support. Neural networks have been used in medical imaging, in medical signal processing and to analyze both clinical and laboratory data. Principally, neural networks simulate the function of the brain. They have to be taught to make correct decisions from the input data. This learning process can be either supervised or unsupervised. The decision making is based on mathematical transformations and it occurs on a hidden level. Calculations are made on parallel manner and the decision making simulates pattern recognition method. Neural networks suit well in medical problems which cannot be defined in simple rules. A drawback of neural networks is that the decisions are irrational and cannot be motivated to the user. Another problem is neural networks' difficulty to handle incomplete input data, i.e., how to define some default or expected values for unknown input parameters. In a complex medical area, which would require multilayered neural networks, the neural networks require a large amount of solved cases for the learning process. In our experience neural networks seem not suitable for diagnosing vertigo and a better choice would be either case-based reasoning or possibly genetic algorithms or a combination of these.

Diagnosis, Computer-Assisted↗