Purpose: To survey the perception, knowledge, wishes, and expectations of Korean radiology residents regarding artificial intelligence (AI) in radiology. Materials and Methods: From June 4th to 7th, 2019, questionnaires comprising 19 questions related to AI were distributed to 113 radiology residents. Results were analyzed based on factors such as the year of residency and location and number of beds of the hospital. Results: A total of 101 (89.4%) residents filled out the questionnaire. Fifty (49.5%) respondents had studied AI harder than the average while 68 (67.3%) had a similar or higher understanding of AI than the average. In addition, the self-evaluation and knowledge level of AI were significantly higher for radiology residents at hospitals located in Seoul and Gyeonggi-do compared to radiology residents at hospitals located in other regions. Furthermore, the self-evaluation and knowledge level of AI were significantly lower in junior residents than in residents in the 4th year of training. Of the 101 respondents, only 16 (15.8%) had experiences in AI-related study while 91 (90%) were willing to participate in AI-related study in the future. Conclusion Organizational efforts through a radiology society would be needed to meet the need of radiology trainees for AI education and to promote the role of radiologists more adequately in the era of medical AI.

Background: Although several characteristics of coronavirus disease 2019 (COVID-19), an ongoing pandemic disease, have been identified, data on the infectivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are limited. Methods: This prospective cohort study was conducted to analyze the infectivity of SARSCoV-2 based on data of all patients diagnosed with COVID-19 confirmed using real-time polymerase chain reaction test from January to April 2020 in Gyeonggi-do, the largest province in Korea. Results: Of the 502 patients, 298 consisting of 106 clusters with 5,909 contacts were included. Of these, 277 (93.0%) were symptomatic, and the most common symptoms were cough, fever, sputum, sore throat, and headache. A total of 94 patients (31.5%) had pneumonia, while 8 (2.7%) died during the follow-up period. The secondary attack rate (SAR) in the study population was 3.5% (204/5,909). In exposure settings, the SAR was higher in religious gathering (13.5% [95% confidence interval, 10.7–16.8%]), workplaces (8.49% [95% CI, 6.08–11.74%]), and schools (6.38% [95% CI, 3.39–11.69%]) than in health care facilities (1.92% [95% CI, 1.45–2.55%]). Sore throat at any period, dyspnea at diagnosis or any period, lower cycle threshold value in the lower respiratory tract samples, leukocytosis, and higher bilirubin levels were associated with higher infectivity of COVID-19. The presence of symptoms was not related to the infectivity. Conclusion In establishing the infection control strategies for COVID-19, the variables associated with high infectivity may be considered.

In preparation for the surge of coronavirus disease 2019 (COVID-19), it is crucial to allocate medical resources efficiently for distinguishing people who remain asymptomatic until the end of the disease. Between January 27, 2020, and April 21, 2020, 517 COVID-19 cases from 13 healthcare facilities in Gyeonggi province, Korea, were identified out of which the epidemiologic and clinical information of 66 asymptomatic patients at the time of diagnosis were analyzed retrospectively. An exposure-diagnosis interval within 7 days and abnormal aspartate aminotransferase levels were identified as characteristic symptom development in asymptomatic COVID-19 patients. If asymptomatic patients without these characteristics at the time of diagnosis could be differentiated early, more medical resources could be secured for mild or moderate cases in this COVID-19 surge.

Background: Escherichia coli is the predominant causative pathogen for community-acquired urinary tract infections (UTIs), and the increase in fluoroquinolone-resistant E. coli is of great concern in Korea. The objectives of this study were to investigate the genotypic characteristics and molecular epidemiology of ciprofloxacin-resistant (CIP-R) E. coli isolated from community-acquired UTIs in Korea. Materials and Methods: E. coli samples isolated from the blood or urine were collected from patients with community-acquired acute pyelonephritis aged 15 years and more who were admitted to 12 Korean hospitals from 1st April 2010 to 29th February 2012. Phylogenetic typing, multilocus sequence typing, and molecular characterization of β-lactamase and plasmidmediated quinolone resistance determinants were performed for CIP-R E. coli isolates. Results: A total of 569 E. coli isolates were collected, and 122 (21.4%) isolates were CIP-R isolates. The most prevalent sequence type (ST) was ST131 (28.7%, 35/122), followed by ST393 (14.7%, 18/122), ST1193 (13.1%, 16/122), ST38 (9.0%, 11/122), and ST405 (8.2%, 10/122). The antimicrobial resistance rates of ST131 to cefepime (22.9%, 8/35), ST38 to gentamicin (100%, 11/11), and ST405 to cefotaxime (66.7%, 6/9) were significantly higher than the resistance rates of all other STs combined. Notably, 40% (4/10) of ST405 clones produced extendedspectrum β-lactamases and were co-resistant to trimethoprim/sulfamethoxazole. aac(6′)-1b-cr (20%, 7/35) and CTX-M-14 (40%, 4/10) were more frequently observed in ST131 and ST405 compared with other clones, respectively. Conclusions Among the CIP-R uropathogenic E. coli isolates in this study, ST131, ST38, and ST405 were specifically associated with antimicrobial resistance.