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您的检索式：作者名="Muhammad Armughan"
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| 1 | Thoracic impalement injury: A survivor with large metallic object in-situ显示文摘Impalement injuries, is a severe form of trauma, which are not common in civilian life. These injuries rarely occurs in major accidents. Abdomen, chest, limbs and perineum are often involved due to their large surface area. Thoracic impalement injury is usually a fatal injury, due to location of major vessels and heart in the thoracic cavity. These injuries are horrifying to site, but the patients who are lucky enough to make it to hospital, usually survive. Chances of survival are larger in right sided impalement injuries while central injuries are always died at the scene.Our patient, 25 years old male, was brought to the emergency room (ER) with large impaled metallic bar (about 2.5 feet long) in situ, in right sided chest. The patient was immediately shifted to operation room (OR) and was operated, his recovery was uneventful without any sequelae.Such patients should be treated and resuscitated according to advanced trauma life support (ATLS) protocols and operated without any delay for further investigations. Such operations are carried out by the most experienced surgeon team available. The impaled objects should not be processed if not necessary to avoid major hemorrhage and damage to vital structures, until the patient is in operation room. Large size and unusual position of impaled objects, makes the job difficult for surgeons/anesthetists.Although horrifying at scene, patients with thoracic impalement injuries are mostly young and healthy, and those who survive the pre-hospital phase are potentially manageable with proper resuscitation. Usually these patients make recovery without any further complications. | Randhawa Muhammad Afzal Muhammad Armughan Muhammad Waqas Javed Usman Ali Rizvi Sajida Naseem | 2018 | Chinese Journal of Traumatology2018，21，6： | 1 |
| 2 | Unordered rule discovery using Ant Colony Optimization显示文摘In this article,a novel unordered classification rule list discovery algorithm is presented based on Ant Colony Optimization(ACO).The proposed classifier is compared empirically with two other ACO-based classification techniques on 26 data sets,selected from miscellaneous domains,based on several performance measures.As opposed to its ancestors,our technique has the flexibility of generating a list of IF-THEN rules with unrestricted order.It makes the generated classification model more comprehensible and easily interpretable.The results indicate that the performance of the proposed method is statistically significantly better as compared with previous versions of AntMiner based on predictive accuracy and comprehensibility of the classification model. | KHAN Salabat BAIG Abdul Rauf ALI Armughan HAIDER Bilal KHAN Farman Ali DURRANI Mehr Yahya ISHTIAQ Muhammad | 2014 | Science China(Information Sciences)2014，57，9： | 1 |
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