Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

Pyogenic granuloma is one of the inflammatory hyperplasia seen in the oral cavity. The
present study included 10 patients with pyogenic granuloma, involving 4 males and 6 females with 1:1.5
male to female ratio. Patient ages ranged from 5 to 85 years (mean, 30 years) and half of the lesions had
pedunculated base, with surface ulceration in 10% of cases. Treatment consisted of resection, using 810
nm diode lasers. Eight patients were anesthetized during the surgical operation by local infiltration of
anesthesia. Only three patients reported mild post-operative pain within the first 24 hours of the healing
period. During the surgical operation there was no significant bleeding so clear surgical field. There was
no blee

Pyogenic granuloma is one of the inflammatory hyperplasia seen in the oral cavity. The
present study included 10 patients with pyogenic granuloma, involving 4 males and 6 females with 1:1.5
male to female ratio. Patient ages ranged from 5 to 85 years (mean, 30 years) and half of the lesions had
pedunculated base, with surface ulceration in 10% of cases. Treatment consisted of resection, using 810
nm diode lasers. Eight patients were anesthetized during the surgical operation by local infiltration of
anesthesia. Only three patients reported mild post-operative pain within the first 24 hours of the healing
period. During the surgical operation there was no significant bleeding so clear surgical field. There was
no blee

Background: Epilepsy is a common neurological disorder of incidence rate 1-2%. Genetic, congenital, developmental, tumors, head trauma and central nervous system infections maybe the cause of epilepsy. This study aimed to determine the prevalence of stomatitis, xerostomia and taste disorder among patients taking carbamazepine or sodium valproate and to make salivary analysis for IgA, cystatin c and salivary flow rate. Material and method:This study performed in al- Yarmuk teaching hospital in Baghdad, Samples consist of (70) epileptics half of them treated with carbamazepine and other half treated with sodium valproate, and (18) healthy control group of both genders and with different ages to detect the prevalence of oral manifestations, s

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the