Purpose: With the accelerated adoption of artificial intelligence (AI) in medicine, the integration of AI education into medical school curricula is gaining significant attention. This study aimed to gather the perceptions of faculty members and students regarding the integration of AI education into medical curricula in the Korean context. Methods: Faculty members and medical students’ perspectives on integrating AI into medical curricula were assessed through thematic analysis of free-written responses from 157 faculty members and 125 students in a national online survey on medical AI competencies in South Korea. Results: Three key themes emerged: content, which prioritizes basic knowledge and its practical applications, with an emphasis on ethical and legal responsibilities; curricular design, which advocates for a spiral curriculum tailored to learners' needs; and concerns, which highlight balancing AI integration with the principal goals of medical education while critically evaluating ongoing advancements. Conclusion Our study adds valuable insights into the content and methods to prioritize AI education. Given the rapid evolution of medical learners and AI technologies, continuous and timely needs assessment for AI curriculum development is crucial to maintain relevance and effectiveness.

Purpose: With the accelerated adoption of artificial intelligence (AI) in medicine, the integration of AI education into medical school curricula is gaining significant attention. This study aimed to gather the perceptions of faculty members and students regarding the integration of AI education into medical curricula in the Korean context. Methods: Faculty members and medical students’ perspectives on integrating AI into medical curricula were assessed through thematic analysis of free-written responses from 157 faculty members and 125 students in a national online survey on medical AI competencies in South Korea. Results: Three key themes emerged: content, which prioritizes basic knowledge and its practical applications, with an emphasis on ethical and legal responsibilities; curricular design, which advocates for a spiral curriculum tailored to learners' needs; and concerns, which highlight balancing AI integration with the principal goals of medical education while critically evaluating ongoing advancements. Conclusion Our study adds valuable insights into the content and methods to prioritize AI education. Given the rapid evolution of medical learners and AI technologies, continuous and timely needs assessment for AI curriculum development is crucial to maintain relevance and effectiveness.

As artificial intelligence (AI) technologies advance and become increasingly integrated into medicine and healthcare services, there is a growing consensus that it is necessary to prepare medical students to understand and utilize AI in medical education. Research and discussions are ongoing regarding the AI competencies that healthcare professionals should have. There are diverse opinions on how to integrate the necessary AI competencies for medical graduates into existing curricula. However, wide agreement exists regarding the importance of providing sufficient and appropriate education on the ethical aspects of using AI in clinical practice and research. In this paper, the authors aim to introduce practical educational principles, strategies, and methods for educators interested in teaching AI ethics in medicine. To achieve this, the paper (1) introduces the AI competencies and medical ethics competencies that medical school graduates should possess; (2) explains the necessity of fostering AI ethics competencies in medical education; (3) discusses the principles of developing AI ethics education and considerations for implementing such curricula; and (4) presents educational modules that can be utilized to cultivate AI ethics competencies in medical students and young physicians. The authors of the paper hope that the case-based module on medical AI ethics we have developed may contribute to prepare medical graduates who are familiar with the principles and guidelines of medical AI ethics, enabling them to make the best ethical choices in any given environment.

Background: Intellectual disability (ID) may be associated with an increased risk of diabetes mellitus (DM). However, evidence from longitudinal studies is scarce, particularly in Asian populations. Methods: This retrospective cohort study used representative linked data from the Korea National Disability Registration System and the National Health Insurance Service database. Adults (≥20 years) who received a national health examination in 2009 (3,385 individuals with ID and 3,463,604 individuals without ID) were included and followed until 2020. ID was identified using legal registration information. Incident DM was defined by prescription records with relevant diagnostic codes. Multivariable-adjusted Cox proportional hazards regression models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) for DM risks in individuals with ID compared to those without ID. Results: Over a mean follow-up of 9.8 years, incident DM occurred in 302 (8.9%) individuals with ID and 299,156 (8.4%) individuals without ID. Having ID was associated with increased DM risk (aHR, 1.38; 95% CI, 1.23 to 1.55). Sensitivity analysis confirmed a higher DM risk in individuals with ID (aHR, 1.39; 95% CI, 1.24 to 1.56) than those with other disabilities (aHR, 1.11; 95% CI, 1.10 to 1.13) or no disability (reference). Stratified analysis showed higher DM risk in non-hypertensive subjects (aHR, 1.63; 95% CI, 1.43 to 1.86) compared to hypertensive subjects (aHR, 1.00; 95% CI, 0.80 to 1.26; P for interaction <0.001). Conclusion Adults with ID have an increased risk of developing DM, highlighting the need for targeted public health strategies to promote DM prevention in this population.

Purpose: The purpose of this study was to develop an approach to alleviate the discomfort caused by sandbag compression after a bone marrow examination. This research examined the effects of applying a pressure hemostasis band on bleeding, pain, and discomfort at the bone marrow examination site. Methods: This study was conducted with a nonequivalent control group non-synchronized design. For 74 patients under evaluation who underwent bone marrow examination, sandbag compression was applied to the examination site in the control group (n=37), and a pressure hemostasis band was applied to the intervention group (n=37). In both groups, absolute bed rest was performed for two hours, and bleeding, pain, and discomfort at the examination site were measured. Results: After two hours of the bone marrow examination, there was no difference in bleeding on the gauze between the two groups (F=0.59, p=.444). Bleeding occurred in three patients in the intervention group and six in the control group (χ 2 =1.14, p=.479), with no cases of hematoma detected in either group. One hour post-examination, the control group experienced significantly higher pain (F=5.45, p=.022) and discomfort (F=5.68, p=.020) than the intervention group. However, pain and discomfort levels were similar between groups after two hours. Conclusion Compared to the sandbag compression group, the band application group showed no difference in bleeding and experienced less pain and discomfort at the examination site. This confirms that the pressure hemostasis band is a suitable alternative to sandbag compression in post-examination care.

As artificial intelligence (AI) technologies advance and become increasingly integrated into medicine and healthcare services, there is a growing consensus that it is necessary to prepare medical students to understand and utilize AI in medical education. Research and discussions are ongoing regarding the AI competencies that healthcare professionals should have. There are diverse opinions on how to integrate the necessary AI competencies for medical graduates into existing curricula. However, wide agreement exists regarding the importance of providing sufficient and appropriate education on the ethical aspects of using AI in clinical practice and research. In this paper, the authors aim to introduce practical educational principles, strategies, and methods for educators interested in teaching AI ethics in medicine. To achieve this, the paper (1) introduces the AI competencies and medical ethics competencies that medical school graduates should possess; (2) explains the necessity of fostering AI ethics competencies in medical education; (3) discusses the principles of developing AI ethics education and considerations for implementing such curricula; and (4) presents educational modules that can be utilized to cultivate AI ethics competencies in medical students and young physicians. The authors of the paper hope that the case-based module on medical AI ethics we have developed may contribute to prepare medical graduates who are familiar with the principles and guidelines of medical AI ethics, enabling them to make the best ethical choices in any given environment.

As artificial intelligence (AI) technologies advance and become increasingly integrated into medicine and healthcare services, there is a growing consensus that it is necessary to prepare medical students to understand and utilize AI in medical education. Research and discussions are ongoing regarding the AI competencies that healthcare professionals should have. There are diverse opinions on how to integrate the necessary AI competencies for medical graduates into existing curricula. However, wide agreement exists regarding the importance of providing sufficient and appropriate education on the ethical aspects of using AI in clinical practice and research. In this paper, the authors aim to introduce practical educational principles, strategies, and methods for educators interested in teaching AI ethics in medicine. To achieve this, the paper (1) introduces the AI competencies and medical ethics competencies that medical school graduates should possess; (2) explains the necessity of fostering AI ethics competencies in medical education; (3) discusses the principles of developing AI ethics education and considerations for implementing such curricula; and (4) presents educational modules that can be utilized to cultivate AI ethics competencies in medical students and young physicians. The authors of the paper hope that the case-based module on medical AI ethics we have developed may contribute to prepare medical graduates who are familiar with the principles and guidelines of medical AI ethics, enabling them to make the best ethical choices in any given environment.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Intellectual disability (ID) may be associated with an increased risk of diabetes mellitus (DM). However, evidence from longitudinal studies is scarce, particularly in Asian populations. Methods: This retrospective cohort study used representative linked data from the Korea National Disability Registration System and the National Health Insurance Service database. Adults (≥20 years) who received a national health examination in 2009 (3,385 individuals with ID and 3,463,604 individuals without ID) were included and followed until 2020. ID was identified using legal registration information. Incident DM was defined by prescription records with relevant diagnostic codes. Multivariable-adjusted Cox proportional hazards regression models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) for DM risks in individuals with ID compared to those without ID. Results: Over a mean follow-up of 9.8 years, incident DM occurred in 302 (8.9%) individuals with ID and 299,156 (8.4%) individuals without ID. Having ID was associated with increased DM risk (aHR, 1.38; 95% CI, 1.23 to 1.55). Sensitivity analysis confirmed a higher DM risk in individuals with ID (aHR, 1.39; 95% CI, 1.24 to 1.56) than those with other disabilities (aHR, 1.11; 95% CI, 1.10 to 1.13) or no disability (reference). Stratified analysis showed higher DM risk in non-hypertensive subjects (aHR, 1.63; 95% CI, 1.43 to 1.86) compared to hypertensive subjects (aHR, 1.00; 95% CI, 0.80 to 1.26; P for interaction <0.001). Conclusion Adults with ID have an increased risk of developing DM, highlighting the need for targeted public health strategies to promote DM prevention in this population.