Knowledge Representation for Health Care: HEC 2016 by David Riaño, Richard Lenz, Manfred Reichert

By David Riaño, Richard Lenz, Manfred Reichert

This e-book constitutes the refereed lawsuits of 2 workshops held on the overseas convention on wellbeing and fitness – Exploring Complexity and clinical Informatics Europe, HEC 2016, held in Munich, Germany, in September 2016: the eighth foreign Workshop on wisdom illustration for future health Care, KR4HC 2016, and the ninth foreign Workshop on Process-oriented details structures in Healthcare, ProHealth 2016.

The eight revised complete papers have been rigorously reviewed and chosen from 12 submissions. The papers are equipped in topical sections on ontologies in future health care; scientific caliber, review, and simulation; laptop directions engineering and utilization; and comorbidity and scientific method management.

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Extra resources for Knowledge Representation for Health Care: HEC 2016 International Joint Workshop, KR4HC/ProHealth 2016, Munich, Germany, September 2, 2016, Revised Selected Papers

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Am. Med. Inform. Assoc. 21(2), 285–291 (2014) 3. : The reproducibility of CLIF, a method for clinical quality indicator formalisation. In: MIE, pp. 113–117 (2012) 4. : Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery. BMC Med. Inf. Decis. Making 14(1), 1 (2014) Formalization and Computation of Diabetes Quality Indicators 35 5. : Analysis and evaluation of the Electronic Health Record standard in China: a comparison with the American national standard ASTM E 1384.

Inform. Assoc. 21(2), 285–291 (2014) 3. : The reproducibility of CLIF, a method for clinical quality indicator formalisation. In: MIE, pp. 113–117 (2012) 4. : Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery. BMC Med. Inf. Decis. Making 14(1), 1 (2014) Formalization and Computation of Diabetes Quality Indicators 35 5. : Analysis and evaluation of the Electronic Health Record standard in China: a comparison with the American national standard ASTM E 1384.

Observe that the current treatment can be null, the first time, but this can be managed by the table (see Fig. 3). The treatment suggested by the table is then stored as the current treatment of the virtual patient, and a new encounter can be synthesized. After synthetization, the type-II table is applied to calculate the evolution of the current signs of the virtual patient from the current signs and the stored treatment. This evolution is modified according to the virtual patient sensitivities in the sensitivity table, and the resulting values stored as the new condition of the virtual patient.

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