Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enhances diagnosis accuracy. Moreover, pharmacokinetic modeling may help optimize therapy and reduce adverse events. Future research should focus on refining risk prediction algorithms that incorporate women-specific cardiovascular risk. Herein, we explore how addressing the burden of CVD in women through precision medicine requires a tailored approach that considers sex-specific risk factors, hormonal influences, biomarkers, and imaging modalities. This review provides a descriptive synthesis of current evidence and highlights existing knowledge gaps and future directions in precision medicine for cardiovascular risk prediction in women.
Mobile phones are widely used nowadays, for different application such as wireless control and monitoring due to its availability and ease of use. The implemented system is based on "global system mobile (GSM)" network by using "short message service (SMS)". The design mainly contains a GSM modem and interfacing unit circuit with microcontrollers. This system could control up to eight different electrical devices such as light, Air conditioner, washing machine and many more applications which needed in daily life in different area (House, Office, or factory, etc.). The control is done by sending a specific SMS messages from traditional or smart phone. The controlling devices are restricted to a pre-defined phone number and are set in the so
... Show MoreThe traditional city suffers from the decline of the urban image due to urban development and homogeneity with the urban context of the city, and because of the lack of determinants governing the urban image, it is that the center of the city of traditional Kadhimiya suffers from a break in the urban image, Therefore, the research included how to build a distinctive urban image of the center of the traditional city of Kadhimiya and achieve the visual pleasure and comfort of the recipient and the urban image here means is an image not picture which are related to several aspects, including physical, social and psychological as well as the collective memory of individuals and their rela
The research deals with a very important issue that affects women, an important segment of the society. This is because women are the basis of the family and the pillar of the society. Thus, the aim of the research is to examine the level and dimensions of the emotional and existential psychological crisis at the sample of the study. It further aims to investigate the statistical significant difference at the level of (0.05) regarding the feeling of the existential psychological crisis among battered and non-battered women. To reveal the objectives of the study, the researcher applied the existential psychological crisis scale to a sample of (72) women, divided into two groups: (35) battered women, who have been chosen purposefully. Thos
... Show MoreLearning a foreign language is a highly interactive process, and a belief that communicative activities foster a great amount of linguistic production provides language practice and opportunities for negotiation of meaning during communicative exchanges. Thus, this study examines what benefits learner-centered classroom setting offers compared with that of teacher–centered classroom, and how less proficient learners accomplish their tasks and activities with scaffolded help during interaction with the help of proficient classmates and under the guidance of a skilful person, i.e., the teacher. The subjects participating in this study are 30 Iraqi 4th year college students in the Department of English, College of Arts , Univer
... Show MoreDoubts arise about the originality of a document when noticing a change in its writing style. This evidence to plagiarism has made the intrinsic approach for detecting plagiarism uncover the plagiarized passages through the analysis of the writing style for the suspicious document where a reference corpus to compare with is absent. The proposed work aims at discovering the deviations in document writing style through applying several steps: Firstly, the entire document is segmented into disjointed segments wherein each corresponds to a paragraph in the original document. For the entire document and for each segment, center vectors comprising average weight of their word are constructed. Second, the degree of cl
... Show MoreMachine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims
... Show More<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
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