Abstract Background Deep learning (DL) has attracted increasing attention in orthodontics, with many studies reporting high diagnostic and predictive accuracy. However, despite these promising results, routine clinical adoption remains limited. Objectives This scoping review aimed to explore the main barriers that restrict the translation of DL systems from research environments into everyday orthodontic practice. Methodology The review was conducted in accordance with PRISMA-ScR guidelines. Electronic searches were performed in PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published between 2015 and June 2025. Studies reporting quantitative performance of DL-based orthodontic applications were included. Dat

Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on

those affected by technological development risks within the scope of medical works. The unprecedented technological development the world witnesses nowadays has been providing brilliant medical service to the human being including examination, diagnosis and the treatment or follow up. However, such works hide behind potential risks threatening people's lives and such risks my be discovered within the limits of now – how and technical knowledge prevailing the time of rendering the medical service. Also this the question is raised on how to keep up between the safety of the patients and such risks are being unknown by the provider and questioning them contradicts the justices. subsequently, can the patients (affected) acquire the compensat

Accountancy unit is looked is upon as unit that established for the purpose achieve it goals and programmers for unlimited time. Unless otherwise take place such as liquation whether voluntary or mandatory.  Thus going concern logic is considered to be the logical foundation witch the familiar accounting principles are based upon.  The future of a Company real its financial statues and position and the extent of it ability to face events in future.  Hence the success and continuity its activities depend on the extent of the company activity to generate profits. And its ability to retain appropriate liquidity to serve its debts.

Therefore financial statements of the company consider to be on

Focal adhesion kinase (FAK), ephrin receptor type A4 (EphA4), and adiponectin (ADPN) are important indicators in inflammation, tumor growth, migration, and angiogenesis in some cancers. The predictive impact of their concentrations in acute myeloid leukemia (AML) patients to be identified remains. The research sought to explore the effect of FAK, EphA4, and ADPN as prognostic biomarkers, and their influence on patient survival, and to look for any potential correlation between their levels with hematological parameters in AML patients.

Conducted two trials separate plants Defla first two seasons, 1998 and 1999 to test the susceptibility Altgveria three varieties including Azharha colored white and pink Qati and pink Qtmr and second seasons 1999 and 2000, two types color Azhaarhama white and pink Qati treated mind half-timbered two types of Alaoxinat IBA and NAA and three concentrations as well as repeatersAdhrt results low Almaah rooting

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.