RESUMO
Background Clear communication of radiological findings is crucial for effective healthcare decision-making. However, radiological reports are often complex with technical terminology, making them challenging for non-radiology healthcare professionals and patients to comprehend. Large language models like ChatGPT (Chat Generative Pre-trained Transformer, by OpenAI, San Francisco, CA) offer a potential solution by translating intricate reports into simplified language. This study aimed to assess the capability of ChatGPT-3.5 in simplifying radiological reports to facilitate improved understanding by healthcare professionals and patients. Materials and methods Nine radiological reports were taken for this study spanning various imaging modalities and medical conditions. These reports were used to ask ChatGPT a set of seven questions (describe the procedure, mention the key findings, express in a simple language, suggestions for further investigation, need of further investigation, grammatical or typing errors, and translation into Hindi). A total of eight radiologists rated the generated content in detailing, summarizing, simplifying content and language, factual correctness, further investigation, grammatical errors, and translation to Hindi. Results The highest score was obtained for detailing the report (94.17% accuracy) and the lowest score was for drawing conclusions for the patient (85% accuracy); case-wise scores were similar (p-value = 0.97). The Hindi translation by ChatGPT was not suitable for patient communication. Conclusion The current free version of ChatGPT-3.5 was able to simplify radiological reports effectively, removing technical jargon while preserving essential diagnostic information. The free version adeptly simplifies radiological reports, enhancing accessibility for healthcare professionals and patients. Hence, it has the potential to enhance medical communication, facilitating informed decision-making by healthcare professionals and patients.
RESUMO
Context: "Foundation course" is an orientation program for MBBS students at time of entry into medical college. Aims: To study the MBBS student's perception of relevance and level of confidence in application of skills acquired in foundation course and its predictors. Settings and Design: A cross sectional study was done among second year MBBS students at a medical college in central Uttar Pradesh, India. Methods and Material: Data was collected online using a Google form over 1 month. About 97 (out of 200) students participated in the study. Final analysis was done for 94 responses. Statistical Analysis Used: Chi Square test for proportions. Results: Overall 83% students found foundation course to be relevant. Sessions on professional development & ethics (94.6%), biomedical waste management (94.6%), social responsibility of doctors (91.5%), communication skill (93.6%), role and responsibilities of Indian Medical Graduate (93.6%), universal precautions (91.5%), immunisation (91.5%) and assessing E -resource (90.4%) were rated as most relevant. Computer skills and sports/extra-curricular activities were perceived as non-relevant by 29% and 16% students respectively. Overall 61% students were confident about application of knowledge/skills acquired in the foundation course. A significant difference was observed for gender and medium of education with regards to level of confidence in application of certain skills/knowledge. Conclusions: Foundation course was perceived as relevant by most students. However, level of confidence with regards to application of skills/knowledge was found to be variable with significant difference for some variables.
