The unexpected death of humans due to a lack of medical care is a serious problem. Additionally, the number of elderly people requiring continuous care is increasing. A global aging population poses a challenge to the sustainability of conventional healthcare systems for the future. Simultaneously, recent years have seen remarkable progress in the Internet of Things (IoT) and communication technologies, alongside the growing importance of artificial intelligence (AI) explainability and information fusion. Therefore, developing smart healthcare systems based on IoT and advanced technologies is crucial. This would open up new possibilities for efficient and intelligent medical systems. Hence, it is imperative to present a prospective vision of smart healthcare systems and explore the key technologies that enable the development of these intelligent medical systems. With smart healthcare systems, the future of healthcare can be significantly enhanced, providing higher-quality care, improved treatment, and more efficient patient care. This paper aims to provide a comprehensive review of the key enabling and innovative technologies for smart healthcare systems. To this end, it will cover the primary goals of each technology, the current state of research, potential applications envisioned, associated challenges, and future research directions. This paper is intended to be a valuable resource for researchers and healthcare providers. Ultimately, this paper provides valuable insights for both industry professionals and academic researchers, while also identifying potential new research avenues.
Regression Discontinuity (RD) means a study that exposes a definite group to the effect of a treatment. The uniqueness of this design lies in classifying the study population into two groups based on a specific threshold limit or regression point, and this point is determined in advance according to the terms of the study and its requirements. Thus , thinking was focused on finding a solution to the issue of workers retirement and trying to propose a scenario to attract the idea of granting an end-of-service reward to fill the gap ( discontinuity point) if it had not been granted. The regression discontinuity method has been used to study and to estimate the effect of the end -service reward on the cutoff of insured workers as well as t
... Show MoreBackground: Acute myeloid leukemia (AML) is a genetically heterogeneous leukemia characterized by abnormal myeloid blast accumulation, disrupting normal hematopoiesis and leading to rapid progression. Objective: To investigate SNPs within the 3’UTR of the CCAAT/enhancer-binding protein alpha (CEBPA) gene and its association with AML in Iraqi patients. Methods: The study was carried out on 120 AML patients classified into newly diagnosed, induction chemotherapy, and consolidation chemotherapy stages (40 each), and 40 individuals as a control group. Genomic DNA was extracted from AML patients and controls, followed by PCR amplification and Sanger sequencing of the 3’UTR region of the CEBPA gene. The AML patients were characterized
... Show MoreThe research aims to identify the academic problems of family counseling diploma students at Saudi Universities. In addition, to identify the differences in these problems according to gender, marital status, place of study, academic specialization, and GPA. The sample consisted of (491) students. The researcher has used one questionnaire for academic problems prepared by the researcher. The research revealed the following results: There were academic problems among family counseling diploma students at Saudi Universities, the most problems were related to the systems and administrations of the university, then the field training, the buildings, classrooms and campus facilities, then the academic courses, after that the exams, then
... Show MoreWireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i
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