Prediction of anastomotic leakage

Background : Anastomotic leakage after esophagectomy is significantly associated with more severe complications, such as sepsis and mortality. Early prediction for anastomotic leakage is usually difficult and needs to be treated rapidly. In the current study, we investigated the correlation between hemodynamic and several complications after esophagectomy in patients with esophageal cancer, using the FloTrac system. Materials and Methods : Between April 2013 and December 2014, 39 patients with a mean age of 66.6 ± 8.9 years underwent postoperative supervision using the FloTrac sensor / Vigileo monitoring system after curative surgery for esophageal cancer. We retrospectively evaluated the association between the number of aberrant cardiac index (CI) along with stroke volume variability (SVV) values and clinicopathological parameters of postoperative complications in this report. Results : There were significant positive correlations between the number of aberrant values of CI along with SVV and depth of invasion during pathological stage. Concerning major postoperative complications, there was a significant positive correlation between the number of aberrant values of CI and anastomotic leakage. Discussion: The hemodynamic change by employing the FloTrac system could predicts the complication of anastomotic leakage after esophagectomy. Adequate management of hemodynamic stability by utilizing it will reduce the complications of anastomotic leakage

Weiying Cheng Ichiro Komura Eddy Current Examination of Fatigue Cracks in Inconel Welds

Basic studies on the eddy current examination of defects i

Graphogenic epilepsy: a variant of language-induced epilepsy distinguished from reading- and praxis-induced epilepsy

AbstractWe report a case of graphogenic epilepsy as a variant of language-induced epilepsy. A 25-year-old, right-handed woman had noticed for the previous 10 years that writing almost always provoked jerks or a jerking sensation in her right hand. No other triggers, including facets of language function such as reading and speaking, elicited any epileptic seizures. Ictal EEG demonstrated an initial left central abnormality. In our report, we stress that graphogenic seizures as an expression of language-induced epilepsy should not be confused with those that are manifestations of juvenile myoclonic epilepsy, and that writing and reading trigger different facets of motor manifestations

Segmentation of stick angle time series

Segmenting stick angle time series data into ``normal'' and ``pre-fall'' sample

Prediction of falls of virtual overdamped stick under human control using machine learning

These figures report the results of a project exploring applicability of a machine-learning-based approach to predicting human error in a simple balancing task. These results are part of the paper <br><br>Zgonnikova, I., Zgonnikov, A., Kanemoto, S. "Stick must fall: Using machine learning to predict human error in virtual balancing task", accepted in Proceedings of IEEE International Conference on Data Mining, Workshop on Data mining for the Analysis of Performance and Success<br