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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.
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CLINICAL DATA: Rituximab is a mouse/human chimeric anti-CD20 IgG1 monoclonal antibody used to treat cancer and autoimmune conditions. Side effects of rituximab include fever, rash, cytopenia and hypotension, back pain, arthralgia, and myalgia. Here, we report on 3 patients who developed moderate to severe tendonitis after the second infusion of rituximab. THERAPEUTIC CHALLENGE: We report 3 patients who developed tendonitis after the second infusion of rituximab. These patients were undergoing treatment for connective tissue diseases. All 3 patients received 2 rituximab infusions, 2 weeks apart. The 3 cases developed clinical tendonitis that was confirmed by magnetic resonance imaging in 2 cases. INTERPRETATION: This is the first case series reporting new onset tendonitis in patients with connective tissue diseases after rituximab therapy. All 3 cases developed tendonitis 1 week after receiving the second dose of rituximab. Clinical features of tendonitis resolved 3-4 months in all cases. The underlying pathogenic mechanism by which rituximab causes tendonitis is not clear, but tendonitis and tendon rupture have been reported after using other medications such as quinolones. The tendon damage was progressive leading to tendon rupture in 1 patient, highlighting the importance of early recognition. It is plausible that there is a cause-effect relation between tendonitis and administration of rituximab in our 3 cases, since none of these cases had previous history of tendonitis; however, more data are needed to confirm this observation.
