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At least 793 records · Page 44Linked to original sources
PubMed1993

The logic of imaging in spine surgery.

Spinal imaging has rapidly evolved into a complex diagnostic field requiring specialized expertise. While many imaging modalities reveal portions of a topographic map of the spine necessary for surgery, only magnetic resonance imaging emerges as the imaging modality of widest and most efficacious first choice. With the increasing high-technology sophistication of modern imaging modalities, the spine surgeon must become completely conversant with the radiologic data produced by these imaging techniques. The authors present a logical approach to spinal imaging--an algorithm--based on etiologic classification and aimed at conserving medical resources and developing an optimal diagnostic pathway for spine injury and disease. Spine surgeons are urged to incorporate the interpretative insights of radiologists into the diagnostic process.

Algorithms↗
PubMed1977

["Search strategy" in solving verbal logic problems by schizophrenic patients].

In a solution of logical tasks of a deductive character by normals and patients with paranoid schizophrenia, the latter find solutions in less than half of the cases. They attract a great amount of questions, the character of which are more concrete with an accent on "weak" signs rather than general. The patients do not display adequate plans in solving such tasks, the search of the semantic field is narrow. Assumingly there is a disorder of the structure and ierarchy of information kept in the brain.

Adult↗
PubMed1996

Logical observation identifier names and codes (LOINC) database: a public use set of codes and names for electronic reporting of clinical laboratory test results.

Many laboratories use electronic message standards to transmit results to their clients. If all laboratories used the same "universal" set of test identifiers, electronic transmission of results would be greatly simplified. The Logical Observation Identifier Names and Codes (LOINC) database aims to be such a code system, covering at least 98% of the average laboratory's tests. The LOINC database should be of interest to hospitals, clinical laboratories, doctors' offices, state health departments, governmental healthcare providers, third-party payors, organizations involved in clinical trials, and quality assurance and utilization reviewers. The fifth release of the LOINC database, containing codes, names, and synonyms for approximately 6300 test observations, is now available on the Internet for public use. Here we describe the LOINC database, the methods used to produce it, and how it may be obtained.

Clinical Laboratory Information Systems↗
PubMedDate not supplied

[Base plate as a logical controller, matching receptor and other functions of bacteriophage T4].

It has been shown that the complex functioning of the baseplate of the bacteriophage T4 is based on the high level hierarchy in the structure organization and on the interaction of protein components forming the hub and the "channels" of short and long fibers. The presence of structure proteins with stabilizing and destabilizing functions has been revealed. It has been shown that the process of binding of long tail fibers with cell receptors is a cooperative process. In general the baseplate can be considered as a logic module providing the transition from the adsorbtion to the nonreversible reorganization in the bacteriophage functioning.

Bacteriophage T4↗
PubMed1995

A case against logic.

Based on a simple example taken from Toxoplasma serology it is shown that employment of formal logic and its symbolic descendants is not always the best choice for supporting medical diagnosis.

Acute Disease↗
PubMed1996

Logic, hermeneutics, and informed consent.

A belief in the validity of informed consent is one of the most important consequences of the doctrine of autonomy in medical ethics. Truly informed consent requires full disclosure of all relevant information by the doctor, competence of the patient to appreciate what the information signifies, understanding of the facts and issues by the patient, a voluntary choice by the patient and an autonomous authorisation for treatment or entry into a trial. Each of these conditions is hard to fulfil. In particular, full autonomy cannot exist in illness, and this is acknowledged by the act of consultation. The issue is further complicated by the stochastic nature of biological systems and the responses to illness and treatment. Disclosure of likely outcomes is, of necessity, unsatisfactory when a patient seeks surety when entering the clinical process with a serious and life threatening disease. Neither strict logic nor the law provide answers to this problem. The legal and moral issues have become confused. This is unfortunate, because the legal concern often centres on avoidance of actions in law rather than on the more fundamental issue of benefit to the patient. There is a need to teach doctors that discussion is a necessary part of the doctor-patient relationship, that fully informed consent is seldom-if ever-possible, and that skill in understanding what the patient is seeking is more important than the development of rigid and legally "complete" consent forms.

Communication↗
PubMed1996

Assessment of a knowledge-acquisition tool for writing Medical Logic Modules in the Arden Syntax.

We have created a tool that allows users unfamiliar with the Arden Syntax and our underlying database to create Medical Logic Modules (MLMs). In a study of this tool (N 16), subjects found it easy to use (mean score - 4.69 on a scale of 1-5, 5 being best). Each subject created 3 MLMs of varying complexity following a protocol. On average, subjects required 312, 308 and 318 seconds, respectively, to complete each MLM. Comparison of clinicians to non-clinicians and those with to those without knowledge of Arden showed no significant difference. Of the 48 MLMs, 47 compiled and executed with appropriate output. Independent manual review of the MLM correlated well and found few errors. We conclude that our tool is easily used by inexperienced persons to write MLMs in the Arden Syntax.

Artificial Intelligence↗
PubMed1975

[Logical analysis of the respective influence of 3 experimental variables using a diagram by L. Carroll. Application of this method to a clinical trial of 2 forms of Noveril].

The analysis of the results gathered in a double-blind randomized cross-over clinical trial of dibenzepine was systematized in order to evidence the relation existing between the experimental variables and the effects measured. The suggested method of analysis is based on logic and makes profit of a diagram by Carroll. This method seemingly permits rigourous and clear conclusions.

Clinical Trials as Topic↗
PubMed1997

Visualizing the logic of a clinical guideline: a case study in childhood immunization.

IMM/Graph is a visual model designed to help knowledge-base developers understand and refine the guideline logic for childhood immunization. The IMM/Graph model is domain-specific and was developed to help build a knowledge-based system that makes patient-specific immunization recommendations. A "visual vocabulary" models issues specific to the immunization domain, such as (1) the age a child is first eligible for each vaccination dose, (2) recommended, "past due" and maximum ages, (3) minimum waiting periods between doses, (4) the vaccine brand or preparation to be given, and (5) the various factors affecting the time course of vaccination. Several lessons learned in the course of developing IMM/Graph include the following: (1) The intended use of the model may influence the choice of visual presentation; (2) There is a potentially interesting interplay between the use of visual and textual information in creating the visual model; (3) Visualization may help a development team better understand a complex clinical guideline and may also help highlight areas of incompleteness.

Child, Preschool↗
PubMed1997

Using Logical Observation Identifier Names and Codes (LOINC) to exchange laboratory data among three academic hospitals.

Using a standard set of names and codes to exchange electronic laboratory data would facilitate multiinstitutional research and data pooling. This need has led to the development of the Logical Observation Identifier Names and Codes (LOINC) database and its test naming convention. We conducted a study which required 3 academic hospitals (in 2 separate medical centers) to extract raw laboratory data from their local information system for a defined patient population, translate tests into LOINC, and provide aggregate data which could then be used to compare laboratory utilization. We found that the coding of local tests into LOINC can often be complex, especially the "Kind of Property" field, and apparently trivial differences in choices made by individual institutions can result in nonmatches in electronically pooled data. In our study, 72-86% of the failures of LOINC to match the same tests between different institutions were due to differences in local coding choices. LOINC has tremendous potential to eliminate the needing for detailed human inspection during the pooling of laboratory data from diverse sites, and perhaps even a built-in capability to adjust matching stringency by selecting subsets of LOINC fields required to match. However, a quality, standard coding procedure at all sites is critical.

Academic Medical Centers↗
PubMed1997

Towards improved knowledge sharing: assessment of the HL7 Reference Information Model to support medical logic module queries.

Because clinical databases vary in structure, access methods and vocabulary used to represent data, the Arden Syntax does not define a standard model for querying databases. Consequently, database queries are encoded in ad hoc ways and enclosed in "curly braces" in Medical Logic Modules (MLMs). However, the nonstandard representation of queries impairs sharing of MLMs, an impediment that has come to be known as the "curly braces problem." As a first step in solving this problem, we evaluated the proposed HL7 Reference Information Model (RIM) as a foundation for a standard query model for the Arden Syntax. Specifically, we analyzed the MLM knowledge base at the Columbia-Presbyterian Medical Center and compared the queries in these MLMs to the RIM. We studied 488 queries in 104 MLMs, identifying 674 total query data elements. Laboratory tests accounted for 45.8% of these elements, while demographic and ADT data accounted for 37.6%. Pharmacy orders accounted for 10.5%, medical problems for 4.3% and MLM output messages for 1.6%. We found that the RIM encompasses all but those data elements signifying MLM output (1.6% of the total). We conclude that the majority of queries in the CPMC knowledge base access a relatively small set of data elements and that the RIM encompasses these elements. We propose extensions of this analysis to continue construction of an Arden query model capable of solving the "curly braces problem."

Artificial Intelligence↗
PubMedDate not supplied

Prognostication of the results of immunosuppressive treatment by means of logical dendrite.

A logical dendrite was designed for establishing indications for immunosupressive treatment; it was applied in a group of 51 patients with rheumatoid arthritis. A nomogram was constructed for calculation of the expected therapeutic result, on the grounds of the indications, proposed duration of treatment and drug dosage. Comparison of the calculated and actual clinical results of treatment showed that in over 80% of cases the actual results were either consistent with or better than the expected ones. The application of prognostication seems to be particularly useful in the case of long-term treatment with highly toxic agents.

Arthritis, Rheumatoid↗
PubMed1998

A "lexically-suggested logical closure" metric for medical terminology maturity.

Medical Terminologies are becoming increasingly expressive secondary to their increase in size, and are becoming increasingly difficult to analyze secondary to inconsistencies in their use and complex interrelationships that are often not explicitly defined. To address these problems, SNOMED-RT is being developed to allow consistent use, and to define explicitly interrelationships between terms. Ensuring the quality of a terminology system like SNOMED-RT presents new challenges which we are trying to address with theoretically-grounded methodologies for quality management. Here we describe an initial metric toward achieving this goal called "lexically-suggested logical closure." We explain how this metric can be useful for tracking the maturity and quality of a terminology, and apply this metric to track the progress of SNOMED-RT development over a portion of its life-cycle.

Algorithms↗