TL;DR: This paper is a report on the first phase of a long-term, interdisciplinary project whose goal is to increase the overall effectiveness of physicians' time, and thus the quality of health care, by improving the information exchange between physicians and patients in clinical settings.

TL;DR: The results reveal that despite the laxity of the encouraging instrument, data from indirect experimentation can yield significant and sometimes accurate information on the impact of a program on the population as a whole, as well as on the particular individuals who participated in the program.

TL;DR: New results in diagnosing pediatric growth trends, updated TrenDx algorithms, and their application to monitoring intensive care unit and pediatric growth data are focused on, and potential application domains for Tren Dx are discussed.

TL;DR: Neural networks which are trained with heart sound classes of greater similarity were found to be less likely to converge to a solution and a prototype normal/abnormal classifier was developed which provided excellent classification accuracy despite the sparse nature of the training data.

TL;DR: In the cases where principal components were used, the artificial neural networks consistently outperformed their linear discriminant counterparts; 100% versus 98% correct classifications for the two class problem and 90% versus 81% for the more complex five class problem.

TL;DR: It is contention that the lack of principled development strategies seriously hampers evaluation and maintenance of the authors' systems, and leads to curtailed system life cycles.

TL;DR: This paper considers the following issues; symbolic representations, plans and actions, distributed cognition, and the transfer of learning in terms of research and theories in clinical cognition and examines the implications for education and training, and for the integration of intelligent systems in medical practice.

TL;DR: A retrospective evaluation of the expert system based on 23,368 hepatitis A and 24,071 hepatitis B serology requests was carried out and a rule pattern matching algorithm based on indexing is internally employed as efficient access method for providing the respective interpretive text.

TL;DR: A new version based on a previous research prototype of NST-EXPERT is described, which infers a diagnosis for each case, elaborates a therapeutic plan, and suggests a prognosis of an early neonatal outcome.

TL;DR: An evaluation of a medical knowledge-based system called VentEx that supports decision-making in the management of ventilator therapy shows that VentEx produced advice of the same quality as the physicians.

TL;DR: The VIA-RAD system (Visual Interaction Assistant for Radiology) is a blackboard-based architecture founded on extensive data collection and analysis in the domain of diagnostic radiology, together with cognitive modeling of the interaction between perception and problem-solving.

TL;DR: The Temporal Control System is described, a programming system designed for building intelligent temporal monitoring programs and the framework for the implementation as well as a method of calculating the 'cost' of different approaches is provided.

TL;DR: The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved.

TL;DR: This paper will show how, even with a very small subset of the information needed to specify a BBN, the IBN is able to carry out predictions about the future blood glucose concentration in a patient by explicitly taking into consideration the level of ignorance embedded in the network.

TL;DR: The situated clinical cognition framework is to allow for moving between models, theories, and perspectives, as it does not presuppose a singular model of clinical thinking.

TL;DR: An intelligent patient monitor named SEPIA is developed to assist clinicians in this task and modeled the medical knowledge as control information to represent the medical actions, and state information is used as feedback control to characterize the patient's state.

TL;DR: A tutorial expert system for neurological clinics which can emulate the diagnostic process of an expert neurologist for neurogenic diseases of the lower limbs, assist users in planning the optimal sequence of NG and EMG tests, interpret the results of these tests, and help users to achieve the most suitable diagnosis.

TL;DR: The goal is to build flexible knowledge-based systems which can use a variety of problem-solving methods and additional task knowledge, without altering the method or task representation, within a problem-space architecture which allows opportunistic adaptation of problems based on the particular goal, situation and knowledge available.

TL;DR: This is the first report in the literature of an algorithm that enumerates all possible mechanisms for reentrant supraventricular tachycardias that use atrioventricular, atriOVentricular nodal, and/or atriofascicular pathways in humans.

TL;DR: This paper describes a prototype framework, named NEUROLAB, dedicated to research and diagnosis in the area of brain disorders, which will provide specific physiological knowledge for solving the so-called inverse problems in electroencephalography (EEG) and magnetoencephalographic (MEG).

TL;DR: A prototype of a knowledge-based system in laboratory medicine that produces report proposals for haematology is presented in this paper, where the medical problem-solving process is modelled with the ST-model (select and test).

TL;DR: The major result of theTERNIST-I project was its knowledge base which has been used in successor systems for medical education and clinical use, and it is concluded that the most successful of them in the near future is likely to be Quick Medical Reference (QMR) when used as an "electronic textbook" of medicine.

TL;DR: It is demonstrated that medical cognition is a collaborative achievement between the physician and the patient and a conceptual model for analyzing such contradictions is presented.

TL;DR: An understanding of professional vision with respect to how physicians use and think about images may aid in developing clinical imaging systems, computer-based patient records, and other clinical information systems that could integrate well with clinical work practice.

TL;DR: The project the authors describe here is aimed at assisting out-patients affected by Insulin Dependent Diabetes Mellitus, and has defined a system built on a two-level architecture based on an adaptive controller, consisting of a Fuzzy Set Controller and an ARX (Autoregressive eXogenous input) Model.

TL;DR: This article presents a case study in constructing a library of reusable ontologies for medical knowledge-based systems by studying the principles that underly the internal structure of the library as well as on the process of constructing and using the library.