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.
The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreNanotechnology is a modern and developed technology, which have great importance in many fields of medicine (diagnosis and treatment). Also, it used to prevent and solve many problems related to animal production and health. The Nanosystems are including metallic nanoparticles, liposomes, polymeric Nanospheres, polymeric micelles, carbon nanotubes, functionalized fullerenes, polymer-coated Nanocrystals, dendrimers and Nanoshells. Our review showed a details classification of nanoparticles and their uses. Nanoparticles have several features depended on the size, colossal surface. The development of antibiotics nanoparticle is very important and has an excellent impact in treating bacterial infections wherever the antibiotics nanopar
... Show MoreA case-control study was designed to find out the association between rs2234671 polymorphism of cxcr1 and rUTI in a sample of Iraqi women by polymerase chain reaction- sequence-specific primer (PCR-SSP) method. The current findings revealed that the genotype GC (OR= 7.86, 95% CI = 2.82-21.87, P= 7.7 × 10-5) and the C allele (OR= 3.93, 95% CI = 1.97 - 7.83, P = 9.8×10-5) are significantly associated with rUTI. However, the genotype GG played as a protective factor (OR= 0.12, 95% CI = 10.05 - 0.34, P = 4.0 ×10-5). Depending on these findings, the genotype GC is significantly associated with rUTI.
Background: Several studies suggested that skeletal system is adversely affected by diabetes and is associated with increased risk of osteoporosis and fragility fractures
Objectives: The study was a case-control study that designed to assess the level of bone turnover markers (BTMs) among patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of body weight and diabetic control on the level of bone turnover
Type of the study: Cross- sectional study.
Methods: The present study included 100 postmenopausal women with type 2 diabetes mellitus. Sixty-six non-diabetic postmenopausal women were enrolled as a control. Fasting b
... Show MoreRadon and its daughters are of the natural radioactive decay of the uranium series. Exposure to radon gas leads to lung cancer, so the risks are significantly higher for smokers than for non-smokers. Therefore, the risk of radon increases for both active and passive smokers. The radioactivity of alpha particles emitted by radium 226, the main source of radon 222, has become harmful because its prevalence and inhalation increase with increased smoking. In this study, a CR-39 detector was used to measure radon, radium, and uranium concentrations and then calculate risk parameters in seven cigarette-smoking females in vitro study of human blood samples, and three normal females with no actual and passive cigarette smoking. The
... Show MoreWhile conservative access preparations could increase fracture resistance of endodontically treated teeth, it may influence the shape of the prepared root canal. The aim of this study was to compare the prepared canal transportation and centering ability after continuous rotation or reciprocation instrumentation in teeth accessed through traditional or conservative endodontic cavities by using cone-beam computed tomography (CBCT).
Forty extracted intact, matured, and 2-rooted human maxillary first premolars were selected for this
The purpose of this research is to a treatment the impact of Views outliers to the estimators of a distributed arrival and service to the theory of queues and estimate the distribution parameters depending on the robust estimators, and when he was outliers greatest impact in the process of estimating the both distributions mentioned parameters, it was necessary to use way to test that does these data contain abnormal values or not? it was used the method ( Tukey ) for this purpose and is of the most popular ways to discover the outliers , it shows that there are views abnormal (outliers ) in the estimators of each of the distributional arrival and service, which have a significant impact on the calculation of these estimato
... Show MoreBACKGROUND: Many genetic factors are known to be related to osteoporosis, and currently the role of the glucagon-like peptide-1 receptor (GLP-1R) gene in bone health has been studied intensively. Some variation of this gene, such as rs1042044 and rs6458093, are known to be linked to metabolic diseases and lower bone mineral density, however their specific contribution to osteoporosis remains largely unexplored. Therefore, this study was conducted to investigate the combined genotypic effect of rs1042044 and rs6458093 as a genetic risk factor for osteoporosis in postmenopausal Iraqi women.METHODS: Blood samples from 75 osteoporosis patients and 75 healthy controls, aged 45-85, were collected. DNA was extracted, and a region of GLP-1R
... Show MoreThere is a natural problem raised by the issue of media performance. As a separate activity and express its own capabilities. This problem can be framed in the form of a question: Is media performance merely a reflection of the activity of other sectors of society, especially political and economic, and what links them to other societal sectors of interrelated relations? Is the media limited to mere transfer, or is it an industry with its own mechanisms and rules? The answer may seem somewhat complicated if we handle media with research and study in general, but the issue may be less complicated when it comes to Arab media, because its data may add another setback to the overall Arab setbacks.
Irisin is a novel myokine and adipokine, its role during pregnancy and its association with some metabolic risk factors especially pre-pregnancy body mass index (pre-BMI) need more evaluation. The aim of the study is to find whether the pre-BMI could predict irisin levels during normal pregnancy and to clarify associations of irisin with some pathological parameters.
Irisin levels were estimated by ELISA in sera of 59 normal pregnant women who enrolled from December 2016 to May 2017 at Maternity Hospital, Zakho city, Kurdistan region (Iraq). Thirty-two normal-weight pregnant (pre-BMI≤24.9 kg/m2, Age=24.03 mean±3.7standard deviation) and 27 overweight/obese-pregnant (pre-BMI>25 kg/m2, Age=27.6 mean±3.9
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