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Biomedical subjects

J A Reggia

Publications and source records attributed to J A Reggia.

17 recordsLinked to original sources
PubMed1991

Modelling acquired dyslexia: a software tool for developing grapheme-phoneme correspondences.

In extending a computer model of acquired dyslexia, it has become necessary to develop a way to group printed characters in a word so that the character groups essentially have a one-to-one correspondence with the word's phonemes (speech sounds). This requires deriving a set of correspondences (legal character groupings, legal associations of character groups with phonemes, etc.) that yield a single grouping or "segmentation" of characters when applied to any English word. To facilitate and partially automate this task, a segmentation program has been developed that uses an interchangeable set of correspondences. The program segments words according to these correspondences and tabulates their success over large sets of words. The program has been used successfully to segment a 20,000 word corpus, demonstrating that this approach can be used effectively and efficiently.

Algorithms↗
PubMed1991

The design and automated testing of an expert system for the differential diagnosis of acute stroke.

Stroke is the third leading cause of death in the United States and a major source of morbidity. [1] Recent studies have shown a potential use for thrombolytic agents in the treatment of ischemic stroke (IS) but these agents are contraindicated in intracerebral hemorrhage (ICH). A computed tomographic scan is used to distinguish between these two stroke types prior to the use of thrombolytic agents, but may not be readily obtainable. Decision making aids such as algorithms developed at Guy's Hospital and Strong Memorial Hospital have been designed in an attempt to make this distinction on clinical grounds. We have constructed computerized medical decision-making (CMD) systems based upon these algorithms and compared their performance to a system we developed with the use of National Stroke Data Bank data. Relevant medical data for each of 337 patient cases in the Mount Sinai Hospital Stroke Data Bank were presented to each of the CMD systems. In consideration of the clinical task of using thrombolytic agents, we attempted to maximize the positive predictive value (PPV) for ischemic stroke. The CMD systems based upon the Guy's Hospital and Mount Sinai algorithms produced PPV's of 95% and 94% with sensitivities of 77% and 78% respectively compared to a PPV of 93% and sensitivity of 56% with the Strong Memorial CMD system. The Mount Sinai CMD system was judged more efficacious than the Guy's Hospital system in that it required less clinical information that could be more easily obtained to arrive at similar results.

Acute Disease↗
PubMed1986

Modelling reading aloud and its relevance to acquired dyslexia.

The cognitive processes underlying reading aloud are generally believed to involve a dual-route print-to-sound mapping. To test this idea, a parallel activation model of reading aloud is being implemented and subjected to experiments. Spread of activation in the model is based on a theory that competition between cognitive processes for limited neurophysiological resources is a fundamental organizing principle of memory retrieval. This paper briefly describes the dual-route print-to-sound mapping, introduces the competition-based theory being tested, and explains our work's relationship to modelling acquired dyslexia.

Artificial Intelligence↗
PubMed1985

Answer justification in medical decision support systems based on Bayesian classification.

Answer justification refers to the ability of a computer program to explain how or why it arrived at a particular conclusion. This paper presents a new method for automated answer justification that is suitable for use in computer-supported decision aids in medicine which are based on Bayesian classification. The factors most responsible for the relative ordering of posterior probabilities of outcomes are identified by analyzing the prior and conditional probabilities used to generate them. This approach is illustrated using a computer decision aid for stroke classification and is seen to produce understandable and clinically plausible explanations.

Computers↗
PubMed1985

Automated classification of phonological errors in aphasic language.

Using heuristically guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work is significant because it introduces and evaluates a novel approach to error simulation and classification, provides a prototype simulation tool for neurolinguistic research, and forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.

Aphasia↗
PubMedDate not supplied

Modeling diagnostic reasoning: a summary of parsimonious covering theory.

Parsimonious covering theory is a formal model of diagnostic reasoning. Diagnostic knowledge is represented in the theory as a network of causal associations, and problem-solving is represented in algorithms that support a hypothesize-and-test inference process. This paper summarizes in informal terms the basic ideas in parsimonious covering theory.

Algorithms↗
PubMedDate not supplied

Feasibility of physician-developed expert systems.

The authors developed an experimental domain-independent "expert system generator" intended for direct use by physicians. They then undertook a four-year study to determine whether physicians could use such a system effectively. During this period they taught the use of the expert system generator to 70 medical students, who utilized it to build two small medical expert systems. At the conclusion of the course, students were examined on decision-making concepts and completed anonymous questionnaires. Performance scores, a composite of test and project grades, were calculated for each student. There was no significant association between previous computer experience and performance score. Thirty-two of 47 students responding felt the expert system generator was easy to use; 15 felt it was of moderate difficulty. Forty-three of 47 thought it a useful teaching aid. These data support the conclusion that physicians can learn to use domain-independent software to implement medical expert systems directly, without a knowledge engineer as an intermediary.

Artificial Intelligence↗
PubMedDate not supplied

Maryland MIRRORS/II: a connectionist model simulator.

Developing and evaluating connectionist models (also called neural models) is a difficult and time-consuming task. To address this issue, we designed a software system called Maryland MIRRORS/II for the construction of connectionist models in biomedicine and other fields. Maryland MIRRORS/II is distinguished from previous and current related systems by its support of a high-level nonprocedural language, a general-purpose event-handling mechanism, and an indexed library of system resources. These features make Maryland MIRRORS/II a convenient software tool for use in biomedicine. This paper describes Maryland MIRRORS/II and provides a simple example in which it uses error back propagation learning to select the appropriate treatment for a given set of manifestations.

Computer Simulation↗