Background: Sickle cell disease (SCD) is a genetic disease that is highly prevalent in Jazan Province, Saudi Arabia, and is mostly characterized by many complications such as vaso-occlusive crises (VOC), acute chest syndrome (ACS) and well-documented neurological complications. These complications may affect patients’ academic performance. Methods: An observational, cross-sectional, retrospective study was conducted in Jazan Province. General and demographic data were collected and questions about academic performance of students with SCD were answered. Both t-tests and chi-square tests, along with multiple logistic regression, were used for analysis. Results: 982 participants were selected for this study with a mean age of 23 years (SD: 7). Most of the participants were female (64%). The number of participants with SCD was 339 (36%), of whom 42% were male. Students with SCD recorded lower grade point averages (GPA) and more absences compared to healthy participants. Further, about 60% of students with SCD thought they performed better than 40% of the participants without SCD during the COVID-19 pandemic when most of the educational activities were online. Conclusion: As has been previously reported, this study suggested that the academic performance of students with SCD is negatively affected compared to healthy individuals, and this is mostly due to complications associated with the disease. Further, students with SCD acknowledged better performance with online education, an option that should be considered to improve their academic performance. National studies on a larger population are required by health and education officials, and supportive online educational programs are warranted to enhance the academic performance of this population.

Background The use of artificial intelligence (AI) in healthcare continues to spark interest and has been the subject of extensive discussion in recent years as well as its potential effects on future medical specialties, including radiology. In this study, we aimed to study the impact of AI on the preference of medical students at Jazan University in choosing radiology as a future specialty. Methodology An observational cross-sectional study was conducted using a pre-tested self-administered online questionnaire among medical students at Jazan University. Data were cleaned, coded, entered, and analyzed using SPSS (SPSS Inc., USA) version 25. Statistical significance was defined as a P-value of less than 0.05. We examined the respondents' preference for radiology rankings with the presence and absence of AI. Radiology's ranking as a preferred specialty with or without AI integration was statistically analyzed for associations with baseline characteristics, personal opinions, and previous exposures among those who had radiology as one of their top three options. Results Approximately 27.4% of males and 28.3% of females ranked radiology among their top three preferred choices. Almost 65.2% were exposed to radiology topics through pre-clinical lectures. The main sources of information about AI for the studied group were medical students (41%) and the Internet (27.5%). The preference of students for radiology was significantly affected when it is assessed by AI (P < 0.05). Around (16.1%) of those who chose radiology as one of their top three choices strongly agree that AI will decrease the job opportunities for radiologists. Logistic regression analysis showed that being a female is significantly associated with an increased chance to replace radiology with other specialty when it is integrated with AI (Crude odds ratio (COR) = 1.91). Conclusion Our results demonstrated that the students’ choices were significantly affected by the presence of AI. Thereover, to raise medical students' knowledge and awareness of the potential positive effects of AI, it is necessary to organize an educational campaign, webinars, and conferences.