Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

DBNRSK Sayed, Journal of Strategic Research in Social Science (JoSReSS), 2020

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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Eighty five samples were taken from patients suffering from pneumonia. Seventy-eight isolates were diagnosed as following: Staphylococcus aureus (23), klebsiella pneumoniae (29), Streptococcus pneumoniae (15), Serratia sp. (4), Haemophilus influenzae (4) and Pseudomonas aeruginosa (3). The clinical isolates were tested for antibiotics sensitivity. They appeared highly resistance to penicillin G and Ampicillin at percentage 89.7 and 84.6% respectly while the results showed highly sensitivity to streptomycin at percentege of (12.8%). To study the antibacterial activity of Alium sativum, Eucalyptus microtheca leaves and Cydonia oblonga seeds extracts, five multi resistant strains were used by using agar well diffusion and disk methods at c

The study aimed to know the effect of the use alcoholic ethanol extraction of Boswellia Carterii In prolonging the period of preservation cooled ground meat in 4C for 6 days, it has been mixing ground meat with 150,300,450 mg/ml of alcoholic extract Consecutive, Where (0 was the control sample), All samples were stored separately for 0 , 3 , 6 days in Refrigerator temperature 4 C, Conducted by some microbial tests, Results have shown that mixing the ground meat with Boswellia Carterii extraction Led to prolong the storage of meat for 6 days at 4 C .and the Best result came when adding alcoholic ethanol extract of Boswellia Carterii by 450mg/ml Which Equal 0.9 g ,that reducing microbial load more higher than 150&300 mg/ml. All of thes