Structure and classification of zoophytes. By James D. Dana.

c. 2

Enhancing text classification to improve information filtering

Text classification, information filtering, semi-supervised learning, quality control

Partially supervised learning of fuzzy classification rules

Fuzzy classification, semi-supervised learning, data mining

Adaptive methods for user-centered organization of music collections

Zugl.: Magdeburg, Univ., Fak. für Informatik, Diss., 2011

Validation of the Killip-Kimball Classification and Late Mortality after Acute Myocardial Infarction

Background: The classification or index of heart failure severity in patients with acute myocardial infarction (AMI) was proposed by Killip and Kimball aiming at assessing the risk of in-hospital death and the potential benefit of specific management of care provided in Coronary Care Units (CCU) during the decade of 60. Objective: To validate the risk stratification of Killip classification in the long-term mortality and compare the prognostic value in patients with non-ST-segment elevation MI (NSTEMI) relative to patients with ST-segment elevation MI (STEMI), in the era of reperfusion and modern antithrombotic therapies. Methods: We evaluated 1906 patients with documented AMI and admitted to the CCU, from 1995 to 2011, with a mean follow-up of 05 years to assess total mortality. Kaplan-Meier (KM) curves were developed for comparison between survival distributions according to Killip class and NSTEMI versus STEMI. Cox proportional regression models were developed to determine the independent association between Killip class and mortality, with sensitivity analyses based on type of AMI. Results: The proportions of deaths and the KM survival distributions were significantly different across Killip class >1 (p <0.001) and with a similar pattern between patients with NSTEMI and STEMI. Cox models identified the Killip classification as a significant, sustained, consistent predictor and independent of relevant covariables (Wald χ2 16.5 [p = 0.001], NSTEMI) and (Wald χ2 11.9 [p = 0.008], STEMI). Conclusion: The Killip and Kimball classification performs relevant prognostic role in mortality at mean follow-up of 05 years post-AMI, with a similar pattern between NSTEMI and STEMI patients.

Prototype-based classification and clustering

Magdeburg, Univ., Fak. für Informatik, Habil.-Schr., 2006

Multimodal automatic user disposition recognition in human-machine interaction

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Emotional and user-specific cues for improved analysis of naturalistic interactions

... ist es nicht möglich, die in dieser Arbeit identifizierten offenen Fragen restlos zu klären. Die Erweiterung der puren akustischen Emotionserkennung durch Berücksichtigung von anderen Modalitäten, Sprechercharakteristiken, Feedbacksignalen und Persönlichkeitsmerkmalen erlaubt es jedoch, länger andauernde natürliche Interaktionen zu untersuchen und dialogkritische Situationen zu erkennen. Technische Systeme, die diese erweiterte Emotionserkennung nutzen, passen sich an ihren Nutzer an und werden so zu seinem Begleiter und letztendlich zu seinem Companion.

Visual analysis, clustering, and classification of contrast-enhanced tumor perfusion MRI data

Magdeburg, Univ., Fak. für Inf., Diss., 2014

Towards effective research-paper recommender systems and user modeling based on mind maps

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Targeted search engines for children : search user interfaces and information-seeking behaviour

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

A tentative classification of the palearctic unionids.

v.24:no.11(1940)

A geographic classification of Neotropical mammals.

v.36:no.6(1958)

On the classification of the histerid beetles, by Rupert L. Wenzel.

v.28:no.2(1944)