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Laparoscopic Surgery Is Associated With Reduced Small Bowel Obstruction Risk After Colorectal Cancer Surgery: A Nationwide Cohort Study of 5458 Patients

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Abbreviated Abstract This nationwide retrospective cohort study of 5458 colorectal cancer surgeries across 32 Japanese institutions examined the effects of laparoscopic surgery, adhesion prevention materials (APMs), and stoma creation on the 5‐year risk of small bowel obstruction (SBO).
Takeshi Yamada   +19 more
wiley   +1 more source
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Bayesian Threshold Estimation

IEEE Transactions on Education, 2009
Bayesian estimation of a threshold time (hereafter simply threshold) for the receipt of impulse signals is accomplished given the following: 1) data, consisting of the number of impulses received in a time interval from zero to one and the time of the largest time impulse; 2) a model, consisting of a uniform probability density of impulse time from ...
Steven C. Gustafson   +4 more
openaire   +2 more sources

Bayesian estimation of unavailability

Reliability Engineering & System Safety, 2004
Abstract This paper gives two Bayesian methods for estimating test-and-maintenance unavailability. Both unplanned and periodic maintenance are considered. One estimation method uses ‘detailed data,’ the individual outage times. The other method uses ‘summary data,’ totals of outage time and exposure time in various time periods such as calendar ...
Corwin L. Atwood, Max Engelhardt
openaire   +2 more sources

BAYESIAN SIGNAL ESTIMATION

Statistics & Risk Modeling, 1996
Summary: The problem of Bayesian estimation of a signal contaminated by white noise is investigated. Restricting the unknown signal to a compact subset of \(L_2 ([0,1])\), the existence of a unique Bayes estimator for the squared-error-loss and its robustness with respect to the prior used are established; for sufficiently diffuse priors, the Bayes ...
Mukherjee, Kanchan, Majumdar, Suman
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Inexact Bayesian estimation

Pattern Recognition, 1992
Abstract Bayesian estimation has many applications in computer vision. A frequent objection to Bayesian estimation is that the probability density functions (pdfs) involved are usually not known exactly. In fact, exact knowledge of the pdfs is not important; it often suffices to know the pdfs approximately. Furthermore, it may even suffice if we have
Mohamed Abdel-Mottaleb, Azriel Rosenfeld
openaire   +1 more source

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