Feature selection is an important task in many problems occurring in pattern recognition, bioinformatics, machine learning and data mining applications. The feature selection approach enables us to reduce the computation burden and the falling accuracy effect of dealing with huge number of features in typical learning problems. There is a variety of techniques for feature selection in supervised learning problems based on different selection metrics. In this paper, we propose a novel unified framework for feature selection built on the graphical models and information theoretic tools. The proposed approach exploits the structure learning among features to select more relevant and less redundant features to the predictive modeling problem according to a primary novel likelihood based criterion. In line with the selection of the optimal subset of features through the proposed method, it provides us the Bayesian network classifier without the additional cost of model training on the selected subset of features. The optimal properties of our method are established through empirical studies and computational complexity analysis. Furthermore the proposed approach is evaluated on a bunch of benchmark datasets based on the well-known classification algorithms. Extensive experiments confirm the significant improvement of the proposed approach compared to the earlier works.

Abstract:This case study concerns a patient with disruption of both tricuspid and aortic valves: a previously healthy, adult man, who sustained a 5-meter fall from a building under construction. The mechanism of the injury was acceleration and deceleration, acting in two different phases of the cardiac cycle, i.e. systole and diastole. Simultaneous occurrence of these injuries is exceedingly rare and in a careful literature review, we did not find any such combination of injury. The possible mechanisms of this injury, as well as surgical techniques are discussed.

The analysis of complaints in different fields of medicine helps understand medical malpractices. This study investigated the complaints related to anesthesia services raised in Kermanshah Medical Council. A total of 35 complaints were found, among which were 16 cases of death and eight cases concluded the malpractice of anesthesiologist. In 21% of cases, the anesthesiologist was found guilty. About half of the complaints and confirmed cases of malpractices pertained to death or permanent brain damage.

Abstract:With an increasing number of off-pump coronary artery surgery procedures in high-risk patients with coagulopathy, including renal failure, hepatic failure and anticoagulant drug-using patients, the frequency of related complications such as repeated exploration for bleeding is also increasing. The associated co-morbidity and repeated use of electrocautery in postoperative bleeding leaves patients susceptible to electrocautery ulcers. In this case series, rare cases of cautery burn with unique causative mechanisms are described.