Systematic reviews in laboratory medicine: principles, processes and practical considerations.

Background: Systematic reviews and meta-analyses are generally accepted to represent the highest level of evidence, and are a cornerstone in practising evidence-based medicine. So far, these efforts have been largely confined to the evaluation of the efficacy and effectiveness of therapeutic and preventive interventions. Systematic reviews in laboratory medicine are scarce and many of them do not meet essential quality criteria [Clin.

Properties and units in the clinical laboratory sciences. V. Properties and units in thrombosis and haemostasis: ISTH-IUPAC-IFCC recommendations 1995.

For historical reasons, the terms used in the nomenclature for properties in thrombosis and haemostasis differ according to 'school' of thought. This hampers communication. In collaboration, The Scientific and Standardization Committee of the International Society on Thrombosis and Haemostasis and the Committee (Commission) of Quantities and Units (in Clinical Chemistry) have prepared a set of recommended systematic names for properties in that domain.

Properties and units in the clinical laboratory sciences. I. Syntax and semantic rules IUPAC--IFCC recommendations 1995.

This document is an updating of previous recommendations on the presentation of properties and their values in clinical laboratory sciences from IFCC, IUPAC and WHO. It forms part of the ongoing effort towards 'standardization' of transmission of laboratory requests and reports across cultural/language domains while avoiding standardization of the language used by clinicians or laboratory practitioners. Subsequent documents will list the kinds-of-property and the properties used in clinical laboratory sciences.

Use of artificial intelligence in analytical systems for the clinical laboratory.

Objective: To consider the role of software in system operation, control and automation, and attempts to define intelligence.

Methods And Results: Artificial intelligence (Al) is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world.