One of the most widespread health issues affecting women is cervical cancer. Early detection of cervical cancer through improved screening strategies will reduce cervical cancer-related morbidity and mortality rates worldwide. Using a Pap smear image is a novel method for detecting cervical cancer. Previous studies have focused on whole Pap smear images or extracted nuclei to detect cervical cancer. In this paper, we compared three scenarios of the entire cell, cytoplasm region, or nucleus region only into seven classes of cervical cancer. After applying image augmentation to solve imbalanced data problems, automated features are extracted using three pre-trained convolutional neural networks: AlexNet, DarkNet 19, and NasNet. There are twenty-one features as a result of these scenario combinations. The most important features are split into ten features by the principal component analysis, which reduces the dimensionality. This study employs feature weighting to create an efficient computer-aided cervical cancer diagnosis system. The optimization procedure uses the new evolutionary algorithms known as Ant lion optimization (ALO) and particle swarm optimization (PSO). Finally, two types of machine learning algorithms, support vector machine classifier, and random forest classifier, have been used in this paper to perform classification jobs. With a 99.5% accuracy rate for seven classes using the PSO algorithm, the SVM classifier outperformed the RF, which had a 98.9% accuracy rate in the same region. Our outcome is superior to other studies that used seven classes because of this focus on the tissues rather than just the nucleus. This method will aid physicians in diagnosing precancerous and early-stage cervical cancer by depending on the tissues, rather than on the nucleus. The result can be enhanced using a significant amount of data.

Background and Aims: A ping pong fracture is a rare depressed skull fracture (DSF) observed in infants. It occurs due to the inward buckling of the calvarium, creating a cup‐like shape. Trauma during childbirth, particularly from instrumental delivery or the application of pressure by physicians or midwives during challenging deliveries, is the primary cause. This study aimed to investigate the epidemiologic characteristics associated with DSF in newborns and to identify the main factors related to its incidence and the type of hematoma involved.Methods: This is a retrospective case‐control analysis of all newborns delivered with DSF at King Abdulla University Hospital in Jordan between January 2008 and December 2020. The medical records were reviewed, and clinical data were collected and analyzed.Results: Out of 42,955 live births delivered at King Abdulla University Hospital, 13 cases of DSF were observed, giving an incidence of 3.0 in 10,000 live births. All cases were delivered at full term. Of the 13 cases, nine cases were associated with the use of instrumental delivery. Seven of those nine cases were delivered vaginally, while the other two cases required cesarean section following unsuccessful instrumental delivery. Four cases were spontaneous, with no history of trauma or instrument use, and delivered by cesarean section. Only 3 of the 13 cases required neurosurgical elevation of DSF. The outcome was excellent in all cases, both cosmetically and neurologically.Conclusion: Ping‐pong skull fractures are seen in newborns infrequently in the Jordanian population, with an incidence of 0.03%. Most of the cases have resulted from difficult deliveries though spontaneous fractures can be encountered rarely. The treatment is usually conservative with spontaneous resolution. The overall prognosis is excellent both neurologically and cosmically.

Second-trimester fetal anomaly scan is an important modality of care in antenatal settings for detecting congenital abnormalities and improving maternal an

Background: This study aimed to identify factors associated with contraceptive method use among married women in Jordan and to examine how sociodemographic, reproductive, and health system variables influence method selection. Methods: A cross-sectional study was conducted between June 2024 and July 2025 across all governorates of Jordan. Data were collected from 400 married women aged 18–48 years across all three regions of Jordan (northern, central, and southern) using a structured questionnaire administered through face-to-face interviews and online surveys ( n = 32). Multivariable binary logistic regression analyses were performed to identify independent predictors of contraceptive method use. Results: Among the 400 participants, 179 (44.8%) reported oral contraceptive pill use, while 167 (41.8%) reported IUD use. Fear of side effects (77.3%) and spousal objection (15.3%) were the primary barriers. Multivariable logistic regression identified younger age (AOR = 0.60, 95% CI: 0.41–0.86), friends as an information source (AOR = 3.59, 95% CI: 1.48–8.70), and access through healthcare centers/hospitals (AOR = 1.99, 95% CI: 1.41–2.81) as significant predictors of oral contraceptive pill use. For IUD use, monthly income (AOR = 1.94, 95% CI: 1.29–2.90), number of children (AOR = 1.92, 95% CI: 1.26–2.94), family as an information source (AOR = 2.55, 95% CI: 1.36–4.79), and fear of side effects (AOR = 2.48, 95% CI: 1.09–5.65) were positive predictors, while previous contraceptive use (AOR = 0.31, 95% CI: 0.20–0.49) and reported complications (AOR = 0.28, 95% CI: 0.14–0.58) were negative predictors, Conclusion: Contraceptive use in Jordan is shaped by a multifactorial combination of demographic, socioeconomic, reproductive, and sociocultural factors. Strengthening evidence-based counseling and addressing social and financial barriers are essential to support informed decision-making and improve maternal and public health outcomes.