Automatic structuring of radiology free-text reports.

A natural language processor was developed that automatically structures the important medical information (eg, the existence, properties, location, and diagnostic interpretation of findings) contained in a radiology free-text document as a formal information model that can be interpreted by a computer program. The input to the system is a free-text report from a radiologic study. The system requires no reporting style changes on the part of the radiologist. Statistical and machine learning methods are used extensively throughout the system. A graphical user interface has been developed that allows the creation of hand-tagged training examples. Various aspects of the difficult problem of implementing an automated structured reporting system have been addressed, and the relevant technology is progressing well. Extensible Markup Language is emerging as the preferred syntactic standard for representing and distributing these structured reports within a clinical environment. Early successes hold out hope that similar statistically based models of language will allow deep understanding of textual reports. The success of these statistical methods will depend on the availability of large numbers of high-quality training examples for each radiologic subdomain. The acceptability of automated structured reporting systems will ultimately depend on the results of comprehensive evaluations.

Requirements of a Web-based experiment management system.

Recent advances in tools for scientific data acquisition, visualization, and analysis have lead to growing information management problems for medical research laboratories. An exponential increase in the volume of data, combined with a proliferation of heterogeneous formats and autonomous systems, has driven the need for flexible and powerful Experiment Management Systems (EMS). This paper provides a detailed analysis of the informatics requirements of an EMS, and proposes a new type of middleware called an EMS-Building Environment (EMSBE), which enables the rapid development of web-based systems for managing laboratory data and workflow. We describe the Web-Interfacing Respository Manager (WIRM), an open-source application server for building customizable experiment management systems. WIRM is being used to manage several ongoing experiments, including a natural language processor of radiological findings, and an interdisciplinary project for studying brain function.

A statistical natural language processor for medical reports.

Statistical natural language processors have been the focus of much research during the past decade. The main advantage of such an approach over grammatical rule-based approaches is its scalability to new domains. We present a statistical NLP for the domain of radiology and report on methods of knowledge acquisition, parsing, semantic interpretation, and evaluation. Preliminary performance data are given. A discussion of the perceived benefit, limitations and future work is presented.