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At least 1,099 records · Page 61Linked to original sources
PubMed1982

Mortality and morbidity in infants less than 1,001 grams birth weight.

A prospective study of 54 infants with birth weights of 1,000 gm or less was conducted over a period of two years. Of the 26 infants who survived, 24 weighed between 750 and 1,000 gm; two infants died after discharge and one was lost to follow-up, leaving 23 in whom serial observations were made over 18 months to 3 years of age. The incidence of neurologic deficit in these infants was 17% and of intellectual deficit, 13%. Of the four who were abnormal neurologically, two had spastic quadriparesis, one static encephalopathy, and one hydrocephalus secondary to intraventricular hemorrhage. The three with intellectual deficit had a developmental quotient less than 85. Of the perinatal factors examined, only birth asphyxia correlated significantly with both neonatal mortality and subsequent morbidity. Six (26%) of the surviving infants had mild, nonblinding retrolental fibroplasia; only one of them had a significant refractive error that required corrective lenses for vision. Sepsis was a significant contributor to neonatal mortality in ten of 28 infants who died, but was detected in only one survivor. Although the prognosis for the infant weighing 1,000 gm or less at delivery has improved significantly, there is promise for still further improvement by reducing perinatal asphyxia.

Asphyxia Neonatorum↗
PubMed1994

The role of object representation in the design of the intelligent radiology workstation.

The paper describes the design of the Intelligent Radiology Workstation (IRW) that is intended to handle heterogeneous radiologic data (text, image, video) and radiologic knowledge in such a way that it is easy to store, access, use, and repurpose. An object-based structure is used to combine the relational database, hybrid knowledge base, and hypermedia within a common framework. Functions such as data entry and retrieval, browsing, and intelligent processing of data are available in the single environment. IRW open architecture allows radiologic digital resources to be used for clinical practice, diagnosis support, education, and research.

Artificial Intelligence↗
PubMed1993

[Neuropsychological outcome of head injury in children].

Wechsler Intelligence Scale for Children-Revised (WISC-R) and Yatabe-Guilford personality test were administered to 31 children who had been hospitalized for head injury and made a GR or MD by the Glasgow Outcome Scale (GOS). The type of lesion, as defined by CT scan categories, was an important factor to prognosticate the outcome of intellectual function. The IQ, especially performance IQ, of acute subdural hematoma (EDH) or severe diffuse brain injury (DBI) was lower than that caused by other types of lesion. Several children demonstrated improvement in IQ level during the initial year. The difference between the IQ of the children who could return to previous school life and that of the children who could not was significant. One of the causes of difficulty in returning to previous school life is decreasing IQ and personality change such as social disadaptability. Neuropsychological evaluation is important in predicting school recovery and deciding proper neuropsychological rehabilitation.

Child↗
PubMed1995

A multi-lingual architecture for building a normalised conceptual representation from medical language.

The overall goal of MENELAS is to provide better access to the information contained in natural language patient discharge summaries (PDSs), through the design and implementation of a prototype able to analyse medical texts. The approach taken by MENELAS is based on the following key principles: (i) to maximise the usefulness of natural language analysis and the usability of its results, the output of natural language analysis must be a normalised conceptual representation of medical information; and (ii) to maximise the reuse of resources, language analysis should be domain-independent and conceptual representation should be language-independent. This paper discusses the results obtained and the issues raised when implementing these principles during the project.

Artificial Intelligence↗
PubMed1995

Real time monitoring in the control theory paradigm.

Monitoring patients hospitalized in hemato-oncology departments to undergo clinical protocols of therapy is a complex task. The main difficulty arises in the follow-up of the oncology protocol and in the management of critical episodes of acute illness which frequently occur due to the high toxicity of the antimitotics used. This problem can be conceptualized within the control theory paradigm as the task of controlling a process whose state can deviate unacceptably from a normal range. Following the control theory analogy at the level of knowledge bases design, we have modeled the medical knowledge as control information to represent the medical actions, and state information is used as a feedback control to readjust the command.

Aged↗
PubMed1995

Design considerations for intelligent data entry: development of MedIO.

Capturing clinical data is a multi-faceted problem. This paper discusses clinical data entry problems encountered during the development of an intelligent clinical data entry system. Based on a review of the problems, recommendations are made for an approach to the design of clinical data entry programs. These recommendations include a discussion of key components in the design process as illustrated by the development of MedIO, a C++ computer program for the entry of history and physical exam information.

Data Collection↗
PubMed1998

Toward information extraction: identifying protein names from biological papers.

To solve the mystery of the life phenomenon, we must clarify when genes are expressed and how their products interact with each other. But since the amount of continuously updated knowledge on these interactions is massive and is only available in the form of published articles, an intelligent information extraction (IE) system is needed. To extract these information directly from articles, the system must firstly identify the material names. However, medical and biological documents often include proper nouns newly made by the authors, and conventional methods based on domain specific dictionaries cannot detect such unknown words or coinages. In this study, we propose a new method of extracting material names, PROPER, using surface clue on character strings. It extracts material names in the sentence with 94.70% precision and 98.84% recall, regardless of whether it is already known or newly defined.

Information Storage and Retrieval↗
PubMed2004

Evolving rule-based systems in two medical domains using genetic programming.

OBJECTIVE: To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. MATERIAL: Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. METHODS: Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. RESULTS: Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. CONCLUSION: The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Aphasia↗