The Clinical Characteristics and Treatment Outcomes of Mesonephric Tumours of the Uterine Cervix: A Systematic Review and Proposal of Embryologically-Oriented Surgical Resection.

: Cervical mesonephric adenocarcinomas (MNACs) are among the rarest neoplasms of the female genital tract. Unlike the majority of cervical cancers, which are predominantly squamous in origin and strongly associated with HPV seropositivity, MNACs are distinct in both histology and pathophysiology. Despite their unique characteristics, MNACs have historically been managed in parallel with squamous cell carcinomas, resulting in a lack of optimised, evidence-based treatment protocols.

Efficacy and Diagnostic Reliability of Intraoperative Frozen Section in the Surgical Management of Early-Stage Cervical Cancer.

Objectives: The aim of this study of this study was to evaluate preoperative radiology and histopathology findings in cervical cancer lymphadenopathy detection, allowing targeted frozen section examination (FSE).

Design: A retrospective analysis was conducted of 203 early-stage cervical cancer patients between 2010 and 2019 in a tertiary centre.

Participants/materials, Setting, And Methods: All patients had histologically confirmed cervical cancer and underwent magnetic resonance imaging (MRI) prior to intraoperative FSE.

Cytoreductive surgery plus chemotherapy versus chemotherapy alone for recurrent epithelial ovarian cancer.

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To evaluate the benefits and harms of secondary CRS and chemotherapy in comparison to chemotherapy alone for women with platinum-sensitive recurrent epithelial ovarian cancer.

The expression of salivary EGF, VEGF, endothelin, and transferrin in waterpipe and cigarette smokers.

The aim of this study was to evaluate the effects of two forms of tobacco smoking, cigarettes and water pipe smoking (WPS), on the expression of a panel of salivary proteins in healthy adults. Three groups of age and gender-matched participants were enrolled in the study: never-smokers, cigarette smokers and WPS (N = 55 per group). Expression of epidermal growth factor (EGF), vascular endothelial growth factor (VEGF), endothelin and transferrin in unstimulated whole saliva was estimated using enzyme-linked immunosorbent assays.

Knowledge of Parents Working in Healthcare Settings Toward Attention-Deficit Hyperactivity Disorder Among Children.

Aim: To examine the knowledge of parents who are working as healthcare workers about Attention-Deficit Hyperactivity Disorder (ADHD) and to determine the predictors of ADHD knowledge in children among parents.

Methods: A cross-section study was conducted among parents who are working as HCWs. An online survey by google forms facilitated the creation of a 373 participant's sample.

Single-cell transcriptomics identifies a WNT7A-FZD5 signaling axis that maintains fallopian tube stem cells in patient-derived organoids.

The study of fallopian tube (FT) function in health and disease has been hampered by limited knowledge of FT stem cells and lack of in vitro models of stem cell renewal and differentiation. Using optimized organoid culture conditions to address these limitations, we find that FT stem cell renewal is highly dependent on WNT/β-catenin signaling and engineer endogenous WNT/β-catenin signaling reporter organoids to biomark, isolate, and characterize these cells. Using functional approaches, as well as bulk and single-cell transcriptomics analyses, we show that an endogenous hormonally regulated WNT7A-FZD5 signaling axis is critical for stem cell renewal and that WNT/β-catenin pathway-activated cells form a distinct transcriptomic cluster of FT cells enriched in extracellular matrix (ECM) remodeling and integrin signaling pathways.

Jordanian Community People's Knowledge of and Attitudes Toward Dementia.

Introduction: Limited research exists on the knowledge and attitudes of Jordanian community residents toward people with dementia (PwD). As the prevalence of dementia is anticipated to increase, there is a critical need for informed knowledge and positive attitudes toward dementia in the Jordanian community.

Objectives: This study aimed to evaluate people's knowledge of and attitudes toward PwD and identify the predictors of dementia knowledge and attitudes.

Spatio-Temporal Cluster Mapping System in Smart Beds for Patient Monitoring.

Innovative technological solutions are required to improve patients' quality of life and deliver suitable treatment. Healthcare workers may be able to watch patients from a distance using the Internet of Things (IoT) by using big data algorithms to analyze instrument outputs. Therefore, it is essential to gather information on use and health problems in order to improve the remedies.

Translation and Validation of the Arabic Version of the Spiritual Perspective Scale.

No valid and reliable instrument exists in Arabic to measure the spiritual perspectives of Arab Muslims and Christians. This study translated the Spiritual Perspective Scale (SPS; Reed, 1987) into Arabic and examined its psychometric properties. The Arabic SPS was tested in a convenience sample of 206 Jordanian Christians and 182 Jordanian Muslim undergraduate nurses.

Automatic Analysis of MRI Images for Early Prediction of Alzheimer's Disease Stages Based on Hybrid Features of CNN and Handcrafted Features.

Alzheimer's disease (AD) is considered one of the challenges facing health care in the modern century; until now, there has been no effective treatment to cure it, but there are drugs to slow its progression. Therefore, early detection of Alzheimer's is vital to take needful measures before it develops into brain damage which cannot be treated. Magnetic resonance imaging (MRI) techniques have contributed to the diagnosis and prediction of its progression.

Application of Deep Learning System Technology in Identification of Women's Breast Cancer.

: The classification of breast cancer is performed based on its histological subtypes using the degree of differentiation. However, there have been low levels of intra- and inter-observer agreement in the process. The use of convolutional neural networks (CNNs) in the field of radiology has shown potential in categorizing medical images, including the histological classification of malignant neoplasms.

Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features.

Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the bone marrow producing many white blood cells (WBC). ALL is one of the most common types of cancer in children and adults. Doctors determine the treatment of leukemia according to its stages and its spread in the body.

Multi-Techniques for Analyzing X-ray Images for Early Detection and Differentiation of Pneumonia and Tuberculosis Based on Hybrid Features.

An infectious disease called tuberculosis (TB) exhibits pneumonia-like symptoms and traits. One of the most important methods for identifying and diagnosing pneumonia and tuberculosis is X-ray imaging. However, early discrimination is difficult for radiologists and doctors because of the similarities between pneumonia and tuberculosis.

Survival Analysis of Oncological Patients Using Machine Learning Method.

Currently, a considerable volume of information is collected and stored by large health institutions. These data come from medical records and hospital records, and the Hospital Cancer Registry is a database for integrating data from hospitals throughout Iraq. The data mining (DM) technique provides knowledge previously not visible in the database and can be used to predict trends or describe characteristics of the past.

Diagnosis of Breast Cancer Using Computational Intelligence Models and IoT Applications.

The use of computer-aided diagnostic (CAD) models has been proposed to aid in the detection and classification of breast cancer. In this work, we evaluated the performance of multilayer perceptron neural network and nonlinear support vector machine models to classify breast cancer nodules. From the contour of 569 samples, ten morphological features were used as input to the classifiers.

Processing Decision Tree Data Using Internet of Things (IoT) and Artificial Intelligence Technologies with Special Reference to Medical Application.

Alternative methods are available for a wide range of medical conditions. Idealistically, doctors would have a tool that would analyse their patients' symptoms and suggest the most accurate diagnosis and treatment plan. Artificial intelligence uses decision trees to predict and classify large datasets.

Diagnosing Cancer Using IOT and Machine Learning Methods.

Breast cancer affects one in every eight women and is the most common cancer. . To diagnose breast cancer, a potentially fatal condition, using microarray technology, large datasets can now be used.

Machine Learning of ZnO Interaction with Immunoglobulins and Blood Proteins in Medicine.

Toxoplasmosis is a zoonotic illness caused by . Those with a normal immune system normally recover without treatment. Immunocompromised individuals and pregnant women must be treated regularly.

Nursing Care Systematization with Case-Based Reasoning and Artificial Intelligence.

Of the most popular applications of artificial intelligence (AI), those used in the health sector are the ones that represent the largest proportion, in terms of use and expectation. An investigative systematization model is proposed in the scientific training of nursing professionals, by articulating epistemological positions from previous studies on the subject. In order to validate the model proposed, a prototype was created to present an application that could help nurses in their clinical processes, storing their experiences in a case base for future research.

Studying the Effects of Cold Plasma Phosphorus Using Physiological and Digital Image Processing Techniques.

The goal of this study is to see how cold plasma affects rabbit bone tissue infected with osteoporosis. The search is divided into three categories: control, infected, and treated. The rabbits were subjected to cold plasma for five minutes in a room with a microwave plasma voltage of "175 V" and a gas flow of "2.

Detection of Emotion of Speech for RAVDESS Audio Using Hybrid Convolution Neural Network.

Every human being has emotion for every item related to them. For every customer, their emotion can help the customer representative to understand their requirement. So, speech emotion recognition plays an important role in the interaction between humans.

The transverse-vertical incision (Alazzam hybrid incision).

Open abdominal surgery evolved around two incisions, vertical and transverse incisions. Transverse incisions are associated with less postoperative morbidities but offer limited access. Vertical incisions offer better access but are associated with more complications.

Artificial Intelligence Technique of Synthesis and Characterizations for Measurement of Optical Particles in Medical Devices.

The aim of this study is to demonstrate the effect of particle size on semiconductor properties; artificial intelligence is being used for the research methods. As a result, we picked cadmium sulfide (CdS), which is a unique semiconductor material that is employed in a broad variety of current applications. Given that CdS has distinct electrical and optical characteristics, it may be employed in the production of solar cells, for example.

Approaches to Federated Computing for the Protection of Patient Privacy and Security Using Medical Applications.

Computing model may train on a distributed dataset using Medical Applications, which is a distributed computing technique. Instead of a centralised server, the model trains on device data. The server then utilizes this model to train a joint model.