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: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

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.

Background/Aims: Autoimmune gastritis (AIG) is a corpus-dominant atrophic gastritis in which patients are positive for antiparietal cell antibody (APCA) and/or anti-intrinsic factor antibody. The risk of developing gastric cancer in patients with AIG remains unclear, and reliable frequency data of AIG in patients with gastric cancer are lacking. Methods: We included 624 Korean patients with gastric tumors (612 gastric cancers and 12 neuroendocrine tumors) who had APCA results and were available for AIG evaluation. In patients with positive APCA results, endoscopy and histology findings were reviewed to diagnose AIG. Results: Of the 624 patients, 37 (5.9%) tested positive for APCA, and ultimately, 11 (1.8%) met the diagnostic criteria for AIG (5 both endoscopy and histology findings, 4 endoscopy-only findings, 2 histology-only findings). The frequency of AIG in patients with gastric cancer was 1.3% (8/612), and that in patients with neuroendocrine tumors was 25.0% (3/12). Of the 11 patients with AIG, serum Helicobacter pylori antibody was positive in six patients (54.5%), all of whom had gastric cancer. Histologically, three patients showed pure AIG, four patients exhibited concurrent AIG and H. pylori gastritis, and the findings for four were indefinite for AIG. The pepsinogen (PG) I levels and PG I/II ratio were significantly lower in patients with gastric cancer with AIG than in patients with gastric cancer without AIG (p=0.042 and p=0.016, respectively). Conclusions The frequency of AIG in gastric cancer patients was very low compared to that in patients with neuroendocrine tumors. Rather, concurrent AIG and H. pylori gastritis was common in patients with AIG with gastric cancer.

Purpose: Thrombosis and bleeding significantly affect morbidity and mortality in myeloproliferative neoplasms (MPNs). The efficacy and safety of direct oral anticoagulants (DOACs) in MPN patients remain uncertain. Materials and Methods: We conducted a large, retrospective, nationwide cohort study using the Korean Health Insurance Review and Assessment Service database from 2010 to 2021. Results: Out of the 368 MPN patients included in the final analysis, 62.8% were treated with DOACs for atrial fibrillation (AF), and 37.2% for venous thromboembolism (VTE). The AF group was statistically older with higher CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes mellitus, prior stroke, transient ischemic attack, or thromboembolism, vascular disease, age 65-74 years, sex category [female]) scores compared to the VTE group. Antiplatelet agents were used in 51.1% of cases, and cytoreductive drugs in 79.3%, with hydroxyurea being the most common (64.9%). The median follow-up was 22.3 months, with 1-year cumulative incidence rates of thrombosis and bleeding at 11.1% and 3.7%, respectively. Multivariate analysis identified CHA2DS2-VASc scores ≥ 3 (hazard ratio [HR], 3.48), concomitant antiplatelet use (HR, 2.57), and cytoreduction (HR, 2.20) as significant thrombosis risk factors but found no significant predictors for major bleeding. Conclusion Despite the limitations of retrospective data, DOAC treatment in MPN patients seems effective and has an acceptable bleeding risk.

Purpose: Some studies suggest that TP53 mutations are associated with the response to immune checkpoint inhibitors (ICI) in patients with non–small cell lung cancer (NSCLC) and also contribute to sex disparities in several cancers. Thus, we hypothesized that TP53 mutations might serve as sex-dependent genomic biomarkers of ICI treatment response in patients with NSCLC. Materials and Methods: Clinical data of 100 patients with metastatic NSCLC treated with ICI monotherapy at Seoul National University Bundang Hospital (SNUBH) were retrospectively reviewed. Genomic and clinical datasets of The Cancer Genome Atlas and an ICI-treated lung cancer cohort (cBioPortal) were also analyzed. Results: In SNUBH cohort, no statistically significant difference was observed in the median progression-free survival (PFS) according to TP53 mutation status (p=0.930); however, female patients with TP53 mutations (MT) had a significantly prolonged median PFS compared to wild-type (WT) (6.1 months in TP53 MT vs. 2.6 months in TP53 WT; p=0.021). Programmed death-ligand 1 (PD-L1) high (≥ 50%) expression was significantly enriched in female patients with TP53 MT (p=0.005). The analysis from publicly available dataset also revealed that females with NSCLC with TP53 MT showed significantly longer PFS than those with TP53 WT (p < 0.001). In The Cancer Genome Atlas analysis, expression of immune-related genes, and tumor mutation burden score in TP53 MT females were higher than in males without TP53 MT. Conclusion Female patients with NSCLC with TP53 mutations had high PD-L1 expression and showed favorable clinical outcomes following ICI therapy, suggesting a need for further research to explore the role of TP53 mutations for sex disparities in response to ICI therapy.

Purpose: Lupus nephritis (LN) can be caused by the complement activation. This study aimed to investigate the differences and clinical implications of the activation pattern of the complement system for pediatric and adult LN patients. Methods: We retrospectively reviewed the medical records of 40 patients (14 pediatric and 26 adult patients) diagnosed with LN through kidney biopsy. Results: The mean ages at diagnosis of pediatric and adult patients were 11.7±2.92 and 37.3±13.5 years, respectively. At the first LN diagnosis, compared with adult patients, pediatric patients had a higher estimated glomerular filtration rate and milder proteinuria; however, there was no statistical significance. The age-adjusted mean serum complement 3 value was significantly lower in the pediatric group (33.0±11.3 mg/dL) than in the adult group (50.8±25.2 mg/dL) (P<0.01). Based on the findings of kidney biopsy, no significant differences were observed in the severity of pathologic classification and the positive rate of complements between adults and children. However, the chronicity index score of adult patients was significantly higher than that of pediatric patients and in the case of complement 4d, despite a similar positive rate, the intensity was significantly stronger for adults (2.35±0.83 vs. 1.54±0.52, (P=0.04). Conclusions The activation pattern of the complement system in LN differs clinicopathologically between pediatric and adult patients and these differences might play an important role in the age-dependent prognosis of LN.