International Journal Papier Advance and Scientific Review

Methods of Diagnosing Immunodeficiency in Adolescents

Ghufran Qasim Abd Alkhaliq — 2024-01-25

Immunodeficiency disorders in adolescents represent a complex and multifaceted challenge in clinical practice. A timely and accurate diagnosis is crucial for appropriate management and improved patient outcomes. This review paper comprehensively examines the methods employed in diagnosing immunodeficiency disorders in adolescents. We explore clinical assessments, laboratory tests, genetic analyses, imaging techniques, and functional assays, highlighting their respective advantages and disadvantages. A critical understanding of these diagnostic approaches equips healthcare professionals with valuable tools to enhance the healthcare of adolescents with immunodeficiency disorders. Furthermore, some systems for diagnosing diseases that affect immunity are explained.

Top Python-Based Deep Learning Packages: A Comprehensive Review

Yasmin Makki Mohialden — 2024-01-25

Deep learning has transformed artificial intelligence (AI) by empowering machines to execute intricate functions with unparalleled precision. The field claims an array of robust packages and libraries, among which Python, a prominent and celebrated programming language, has emerged as a pivotal choice for deep learning study and development. Python has become a leading language in deep learning due to its simplicity and the vast array of libraries available for developers and researchers. This article thoroughly examines the most broadly adopted deep learning packages within the Python system. The packages under scrutiny include TensorFlow, PyTorch, Keras, Theano, and Caffe. We exactly assess each of these packages to establish their typical features and capabilities. Moreover, the review explores into an in-depth analysis of the assets and weaknesses inherent in each package. This detailed exploration prepares readers with the information necessary to make informed decisions regarding the variety of the most suitable packages custom-made to their specific needs. This comprehensive review aims to propose a nuanced understanding of the landscape of popular deep learning packages and support practitioners and researchers in creation strategic and well-informed choices for their deep learning actions.

Effectiveness of Early Mobilization and Administration of Cork Fish Extract on Wound Healing of Sectio Caesarean Surgery at Noemuti Health Center

Fitriyaningsih Fitriyaningsih — 2024-02-23

This study aims to determine the effectiveness of early mobilization and administration of cork fish extract on wound healing after Sectio caesarea surgery at Puskesmas Noemuti. The problem faced is the high rate of cesarean delivery in Indonesia which can cause complications such as surgical wound infection and increase maternal and infant mortality. The method used is a type of quasy experimental research with a static group comparison design approach. The results showed that early mobilization and administration of cork fish extract were effective in improving sectio caesarean wound healing. The treatment group given the intervention of early mobilization and administration of cork fish extract had a better level of surgical wound healing compared to the control group which was only given the standard hospital intervention. This study can contribute to improving the quality of health services in Indonesia, especially in the handling of labor through cesarean section.

Factors Influencing the Use of Long-Term Contraceptive Methods at the Noemuti Health Center, North Central Timor District

Flora Naibaho — 2024-02-23

Examining the factors that influence the utilization of Long-Term Contraceptive Methods (MKJP) at the Noemuti Health Center in the North Central Timor District is the purpose of this research. The principal issue is the inadequate utilization of MKJP, one of the safest and most effective contraceptives.This research employed a quantitative methodology and a cross-sectional design. In 2021, the entire active family planning acceptor population at the Noemuti Health Center in North Central Timor Regency comprised the study population of 1,899 individuals. As indicated by the results, the proportion of the low education variable that utilized MHJP was 36.8%, whereas the high education variable accounted for 33.3%. In relation to the use of MHJP, the employment variable revealed that 43.9% of acceptors who were employed utilized MHJP, whereas the employment variable of those who were unemployed utilized MHJP. The statistical analysis indicated that age, occupation, and level of education did not have a statistically significant impact on the utilization of MHJP. Nevertheless, the hypothesis was validated as the statistical data revealed that mothers with a higher level of education exhibited a greater utilization of contraceptives. This research offers valuable insights that can be utilized to bolster the family planning initiative and promote greater utilization of MHJP in Puskesmas Noemuti, North Central Timor District.