Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study.

BACKGROUND: Emerging artificial intelligence (AI) technologies have diverse applications in medicine. As AI tools advance towards clinical implementation, skills in how to use and interpret AI in a healthcare setting could become integral for physicians. This study examines undergraduate medical students' perceptions of AI, educational opportunities about of AI in medicine, and the desired medium for AI curriculum delivery. METHODS: A 32 question survey for undergraduate medical students was distributed from May-October 2021 to students to all 17 Canadian medical schools. The survey assessed the currently available learning opportunities about AI, the perceived need for learning opportunities about AI, and barriers to educating about AI in medicine. Interviews were conducted with participants to provide narrative context to survey responses. Likert scale survey questions were scored from 1 (disagree) to 5 (agree). Interview transcripts were analyzed using qualitative thematic analysis. RESULTS: We received 486 responses from 17 of 17 medical schools (roughly 5% of Canadian undergraduate medical students). The mean age of respondents was 25.34, with 45% being in their first year of medical school, 27% in their 2nd year, 15% in their 3rd year, and 10% in their 4th year. Respondents agreed that AI applications in medicine would become common in the future (94% agree) and would improve medicine (84% agree Further, respondents agreed that they would need to use and understand AI during their medical careers (73% agree; 68% agree), and that AI should be formally taught in medical education (67% agree). In contrast, a significant number of participants indicated that they did not have any formal educational opportunities about AI (85% disagree) and that AI-related learning opportunities were inadequate (74% disagree). Interviews with 18 students were conducted. Emerging themes from the interviews were a lack of formal education opportunities and non-AI content taking priority in the curriculum. CONCLUSION: A lack of educational opportunities about AI in medicine were identified across Canada in the participating students. As AI tools are currently progressing towards clinical implementation and there is currently a lack of educational opportunities about AI in medicine, AI should be considered for inclusion in formal medical curriculum.

Transfixing heart injury by stab wound: Case report.

Cardiac impalement is a rare and usually fatal injury. Immediate recognition and surgical intervention are decisive factors for patient survival. This is a reported case of cardiac impalement with left ventricular transfixation, whose prehospital management, surgical treatment and postoperative care were successful.

Impact of the COVID-19 pandemic in patient admission to a high-complexity cancer center in Southern Brasil.

OBJECTIVE: The aim of our study was to investigate whether there has been a reduction in patient admission to a high-complexity cancer care center in Brasil during the COVID-19 pandemic, similar to what was reported in Europe. METHODS: We reviewed the cancer tracking database of the largest cancer center in southern Brasil and performed statistical tests to compare first-time appointments from the onset of the outbreak until the end of June to those of the equivalent period in 2019. RESULTS: We observed a dramatic reduction (-42%) in first-time appointments during the pandemic compared to the same period in the previous year (P <0.001). This reduction was observed among all medical specialties (P <0.001). CONCLUSION: The onset of COVID-19 was correlated with a reduction in admission to a high-complexity cancer care center in Brasil. Since a delay in diagnosis and treatment may influence prognosis, it is important that cancer centers and public health strategies reinforce care for non-COVID-19 patients to prevent potentially unnecessary deaths.

Impact of the COVID-19 pandemic in patient admission to a high-complexity cancer center in Southern Brasil

SUMMARY OBJECTIVE: The aim of our study was to investigate whether there has been a reduction in patient admission to a high-complexity cancer care center in Brasil during the COVID-19 pandemic, similar to what was reported in Europe. METHODS: We reviewed the cancer tracking database of the largest cancer center in southern Brasil and performed statistical tests to compare first-time appointments from the onset of the outbreak until the end of June to those of the equivalent period in 2019. RESULTS: We observed a dramatic reduction (-42%) in first-time appointments during the pandemic compared to the same period in the previous year (P <0.001). This reduction was observed among all medical specialties (P <0.001). CONCLUSION: The onset of COVID-19 was correlated with a reduction in admission to a high-complexity cancer care center in Brasil. Since a delay in diagnosis and treatment may influence prognosis, it is important that cancer centers and public health strategies reinforce care for non-COVID-19 patients to prevent potentially unnecessary deaths.