The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

OBJECTIVE: To determine the preferred specialties of graduated medical doctors working in Basra, and determine the factors behind their preferences. METHODS: The study was conducted in 38 primary health care centres and seven hospitals in Basra from January-June 2014. A cross-sectional study was adopted with the use of a self-administered questionnaire form. Two hundred ninety six graduated doctors were agreed to participate. Chisquare test and logistic regression were used to test the association between deciding a future speciality and influencing factors. RESULTS: The most preferred specialties were radiology and ultrasound, gynaecology and obstetrics, surgery, internal medicine, dermatology and paediatrics. Clinical specialties were sta

High frequencies of multidrug resistant organisms were observed worldwide in intensive care units which is a warning as to use the only few effective antimicrobials wisely to reduce selective pressure on sensitive strains.

The aim of the current study is to asses the compliance of the currently followed antibiotic prescribing pattern in the intensive care unit in an Iraqi hospital with the international guidelines.A cross-sectional study was done in the intensive care unit (ICU) of the Surgical Specialties Hospital, Medical City in Bagdad from the 30^th of November 2011 to the 5^th of May 2012.Patients were followed until they were discharged or died to see any change in condition, response to drugs, devices u

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

Background: Self-medication is a practice or action taken by individuals for themselves in order to achieve and maintain health, as well as to avoid and protect against disease. The aim of this study is to evaluate the knowledge, attitudes, and practice of self-medication among medical students at Sudan International University.

Subjects & Methods: This was a prospective study that involved 288 out of 1000 students in the Faculty of Medicine at Sudan International University. Data were collected using a self-administered questionnaire from January to March 2022 to evaluate the self-medication knowledge, attitude, and practice among first, second, and third-ye

تشغل الفضاءات الداخلية الطبية اهتمام واسع , لما توفره من رعاية صحية للمرضى ,فلابد ان يُهتَمْ بها من الجانب الوظيفي(الادائي), لتحقيق الراحة البصرية والنفسية والجسدية لغرض الوصول الى الاداء الجيد للكادر الطبي, ولهذا وجد ضرورة التعرف على تلك الفضاءات الداخلية بشكل اعمق , وهل انها ملاءمة للمرتكزات التصميمية المتعارف عليها؟ , لذلك تم تسليط الضوء على الفضاءات الداخلية للمختبرات الطبية, وقد تناول البحث المشكلة واه

Thirty swabes of medical implants were collected from Al-Yarmouk's hospital which were cultured on manitole agar to isolate Staphelococcus aureus . Only four samples gave positive results with this media. It was used ten types of antibiotics to test the sensitivity of this bacterium against them. All isolates of S. aureus were recorded as multidrug resistant and were considered as MRSA. One pledge alternative therapy is the utilize of certain pure bacterocin MIC (32.5 to 62.5 μg/ml) and it was compared with vancomycin (200-400 μg/ml) with average of (8 – 15) mm diameter of inhibition zones recpectively. The first reduction of biofilm formation ability has been proved in catheters when treatedby pure bacterocin. The test shows the highes

BACKGROUND: The humeral shaft fractures have a good rate of union, despite this fact, still there is a significant rate of nonunion after nonoperative treatment and more often after operative treatment. AIM: The aim of the study is to evaluate the autogenous onlay graft with compression plate for treatment of persistent humeral shaft non-union with failed previous surgery both radiological and functional outcome. MATERIALS AND METHODS: A prospective study on twenty patients having persistent aseptic non-union age between 20 and 60 years old, after failed surgical treatment of fractures humeral shaft in Al-Zahra teaching and Al-Kindy teaching hospitals, while infected nonunion, diabetes mellitus, secondary metastasis, smoking, a

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c