The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

     Ovarian cancer is a heterogeneous disease with disparities in clinical performance and consequences. It is a cluster of numerous subtypes with diverse biological topographies that cause alterations in response to treatments, relapse rates, and endurance. This task was designed to investigate the epidemiology of the diagnosed cases of ovarian cancer from 2014 to 2020 in Baghdad. A total of 51 cases of different ovarian cancer samples were collected from Al-Elwea Maternity Hospital and Medical City Teaching Hospital, Baghdad. Clinical information including patients' age, tumor size and location, pathological grade and stage were also collected. Results revealed high incidence of OC in patients at age of ˂55 years for the rate 59%

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Background: Fenugreek herb is one of the most abundant plants in our country. The dried ripe seeds of this plant are the effective medicinal part the plant.
Aim of the work: The aim of this study is to determine the pharmacological effect of a new chemical substance that has been extracted from crude fenugreek seeds which has a hormonal like action and to assess the safety of this experimental material in order to recommend it in future as a stimulator for ovulation or a contraceptive pill.
Materials and Methods: Sixty uncoupled female rats and mice were enrolled in this study, categorized into groups as mentioned in the text. Prolactin, estradiol and progesterone serum levels where measured for all gr

Cyprinidae species are the most abundant and widely distributed fish species in the inland waters of Iraq. Cyprinids are complex species, and it is difficult to identify them on the basis of morphology. Thus, the morphological characteristics must be achieved and confirmed by molecular analysis. Twenty specimens of Cyprinion kais Heckel, 1843 (Piscies, Cypriniformes, Cyprinidae) were collected from two localities at Tigris River in the middle of Iraq: five specimens from Al-Tharthar Lake, Saladin Province, and 15 specimens from Al- Zubaydiyah sub-district, Wasit Province