Automated data extraction of electronic medical records: Validity of data mining to construct research databases for eligibility in gastroenterological clinical trials.

BACKGROUND: Electronic medical records (EMRs) are adopted for storing patient-related healthcare information. Using data mining techniques, it is possible to make use of and derive benefit from this massive amount of data effectively. We aimed to evaluate validity of data extracted by the Customized eXtraction Program (CXP). METHODS: The CXP extracts and structures data in rapid standardised processes. The CXP was programmed to extract TNFα-native active ulcerative colitis (UC) patients from EMRs using defined International Classification of Disease-10 (ICD-10) codes. Extracted data were read in parallel with manual assessment of the EMR to compare with CXP-extracted data. RESULTS: From the complete EMR set, 2,802 patients with code K51 (UC) were extracted. Then, CXP extracted 332 patients according to inclusion and exclusion criteria. Of these, 97.5% were correctly identified, resulting in a final set of 320 cases eligible for the study. When comparing CXP-extracted data against manually assessed EMRs, the recovery rate was 95.6-101.1% over the years with 96.1% weighted average sensitivity. CONCLUSION: Utilisation of the CXP software can be considered as an effective way to extract relevant EMR data without significant errors. Hence, by extracting from EMRs, CXP accurately identifies patients and has the capacity to facilitate research studies and clinical trials by finding patients with the requested code as well as funnel down itemised individuals according to specified inclusion and exclusion criteria. Beyond this, medical procedures and laboratory data can rapidly be retrieved from the EMRs to create tailored databases of extracted material for immediate use in clinical trials.

Underwater hyperspectral imaging: a new tool for marine archaeology.

By applying an underwater hyperspectral imager (UHI) to a selection of archaeological artifacts, we have found spectral signatures that are representative of materials likely to be present at wreck sites. By successfully using the signatures to classify a subset of said artifacts placed on the seabed at 61 m depth, we demonstrate that it is possible to detect archaeological objects of interest in UHI data acquired by a remotely operated vehicle. Correct UHI classification of rust and glass bottles in situ on a historical wreck site further supports the viability of the method for marine archaeological applications.

Integrated environmental mapping and monitoring, a methodological approach to optimise knowledge gathering and sampling strategy.

New technology has led to new opportunities for a holistic environmental monitoring approach adjusted to purpose and object of interest. The proposed integrated environmental mapping and monitoring (IEMM) concept, presented in this paper, describes the different steps in such a system from mission of survey to selection of parameters, sensors, sensor platforms, data collection, data storage, analysis and to data interpretation for reliable decision making. The system is generic; it can be used by authorities, industry and academia and is useful for planning- and operational phases. In the planning process the systematic approach is also ideal to identify areas with gap of knowledge. The critical stages of the concept is discussed and exemplified by two case studies, one environmental mapping and one monitoring case. As an operational system, the IEMM concept can contribute to an optimised integrated environmental mapping and monitoring for knowledge generation as basis for decision making.