Background: Artificial intelligence (AI) is rapidly evolving with the potential to revolutionize various aspects of healthcare. Despite the increasing use of AI in medicine, research on the knowledge and attitudes of medical students towards AI remains limited. Aim: This study aims to evaluate the level of knowledge and attitude towards AI and its use in medical education and future medical practice among Ain Shams University undergraduate medical students. Methods: A Cross-sectional study using a self-administered questionnaire. Results: A total of 410 medical students completed the questionnaire. The mean age of participating students was 19.7 ± 1.5, of which 56.1% were females. Students in the first and second years represented 75.3% of the total participating students. Most of the students demonstrated moderate (41.2%) to good (57.7%) knowledge and attitude regarding AI and its application in medical education, and similarly moderate (67.5%) to good (28.9%) knowledge and attitude regarding AI and its application in medical practice. Over 80% of students emphasized the need to integrate teaching about AI in their medical curricula and thought that AI will soon revolutionize education. In addition, over 85% showed enthusiasm to learn about the applications of AI in medicine. Conclusion: The findings from the current study highlight the crucial need for medical schools to adapt to the changing technology and ensure that future physicians are ready for these changes. Medical curricula must evolve to prepare students effectively by providing comprehensive knowledge and understanding of AI and its applications, ensuring students are well-prepared for their future careers.
Poisoning and fatalities by cardiotoxic agents represent a challenging health problem in Egypt. An important action to combat this problem is to predict or, at least, early diagnose cardiac involvement. To do so, the clinician needs both bedside skills and appropriately selected laboratory testing. The Poisoning Severity Score (PSS) has been evaluated in one study which found it to be useful in identifying serious and complicated cases of poisoning. The aim of this study was to investigate effectiveness of the PSS in predicting cardiotoxicity, as well as correlations of different demographic, exposure, clinical and laboratory findings to cardiotoxicity. Methodology: Over a period of 4 months, we investigated 59 patients with anticholinesterases (n=28), digoxin (n=17), and beta-blocker toxicities (n=14) admitted to Poison Control Center of Ain Shams University Hospitals (PCCA), Cairo, Egypt, in addition to 16 healthy controls. For each, age, sex, mode of exposure, compound involved, time elapsed between exposure and admission, length of hospital stay, clinical, laboratory, and electrocardiographic findings were recorded. Also, PSS was calculated. Results: Female gender, lag between exposure and admission, length of ICU stay, and total length of hospital stay were significantly correlated to the severity of cardiotoxicity. Vomiting, metabolic acidosis, respiratory alkalosis, and PSS were independent predictors of cardiotoxicity. A PSS of 2 had a sensitivity of 88% and a specificity of 64.7% in predicating cardiotoxicity. Conclusion: Implication of PSS in prediction and early diagnosis of cardiotoxicity is easy, available, cheap, and reliable, whatever the type of toxic exposure.
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