• Journal of Gastric Cancer
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• v.23 no.3
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• pp.388-399
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• 2023

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

• Clinics in Shoulder and Elbow
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• v.27 no.1
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• pp.108-116
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• 2024

Reverse total shoulder arthroplasty (RTSA) is widely popular among shoulder surgeons and patients, and its prevalence has increased dramatically in recent years. With this increased use, the indicated pathologies associated with RTSA are more likely to be encountered, and challenging patient presentations are more likely to be seen. One prominent challenging presentation is RTSA patients with severe glenoid bone loss. Several techniques with varying degrees of invasiveness, including excessive reaming, alternate centerline, bone grafting, and patient-specific implants (PSIs), have been developed to treat patients with this presentation. PSI treatment uses a three-dimensional reconstruction of a computed tomography scan to design a prosthetic implant or component customized to the patient's glenoid morphology, allowing compensation for any significant bone loss. The novelty of this technology implies a paucity of available literature, and although many studies show that PSIs have good potential for solving challenging shoulder problems, some studies have reported questionable and equivocal outcomes. Additional research is needed to explore the indications, outcomes, techniques, and cost-efficiency of this technology to help establish its role in current treatment guidelines and strategies.

• Quality Improvement in Health Care
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• v.5 no.1
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• pp.120-127
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• 1998

Background : This study is to identify preoperative patient characteristics associated with a lack of improvement on one or more measures peri operatively, postoperative 3-4 months, and postoperative 12 months. Methods : For the assessment, prospective study was performed with 92 patients who had undergone either one eye or both eye cataract surgery by 3 ophthalmologists practicing at a university hospital. The criteria of improvement were (1) Snellen visual acuity, (2) a cataract-related symptom score(possible range: 0, 0 of 6 symptoms present or bothersome, to 18, all 6 symptoms very bothersome), and (3) VF-14 score - a measure of functional impairment in patient with cataract - (possible range: 0, inability to perform any of the applicable activities, to 100, no difficulty in performing any of the applicable activities). Results : Although 14 patients (15.2%) failed to improve on one or more of the outcome measures assessed, no one failed to improve on all three measures. Both eyes of surgery than one eye, preoperative cataract symptom score of 1-4, 5 or higher than 0 were associated independently with the increased likelihood of improvement (odds ratio 8.95, 7.16, 8.87 respectively). And the preoperative level of Snellen visual acuity was not associated with the likelihood of improvement Conclusion : We conclude that specific preoperative characteristics (both eyes, cataract symptom score) are independent predictors of patient outcome after cataract surgery.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.442-453
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• 2021

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and prediction. Discrimination accuracy of AI algorithms is often evaluated with the Dice similarity coefficient, sensitivity, specificity, and traditional or free-response receiver operating characteristic curves. Calibration accuracy should also be assessed, especially for algorithms that provide probabilities to users. As current AI algorithms have limited generalizability to real-world practice, clinical validation of AI should put it to proper external testing and assisting roles. External testing could adopt diagnostic case-control or diagnostic cohort designs. A diagnostic case-control study evaluates the technical validity/accuracy of AI while the latter tests the clinical validity/accuracy of AI in samples representing target patients in real-world clinical scenarios. Ultimate clinical validation of AI requires evaluations of its impact on patient outcomes, referred to as clinical utility, and for which randomized clinical trials are ideal. Device approval of AI is typically granted with proof of technical validity/accuracy and thus does not intend to directly indicate if AI is beneficial for patient care or if it improves patient outcomes. Neither can it categorically address the issue of limited generalizability of AI. After achieving device approval, it is up to medical professionals to determine if the approved AI algorithms are beneficial for real-world patient care. Insurance coverage decisions generally require a demonstration of clinical utility that the use of AI has improved patient outcomes.

• Journal of Preventive Medicine and Public Health
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• v.53 no.6
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• pp.447-454
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• 2020

Objectives: The aim of the present study was to investigate the relationships among hospital safety climate, patient safety climate, and safety outcomes among nurses. Methods: In the current cross-sectional study, the occupational safety climate, patient safety climate, and safety performance of nurses were measured using several questionnaires. Structural equation modeling was applied to test the relationships among occupational safety climate, patient safety climate, and safety performance. Results: A total of 211 nurses participated in this study. Over half of them were female (57.0%). The age of the participants tended to be between 20 years and 30 years old (55.5%), and slightly more than half had less than 5 years of work experience (51.5%). The maximum and minimum scores of occupational safety climate dimensions were found for reporting of errors and cumulative fatigue, respectively. Among the dimensions of patient safety climate, non-punitive response to errors had the highest mean score, and manager expectations and actions promoting patient safety had the lowest mean score. The correlation coefficient for the relationship between occupational safety climate and patient safety climate was 0.63 (p<0.05). Occupational safety climate and patient safety climate also showed significant correlations with safety performance. Conclusions: Close correlations were found among occupational safety climate, patient safety climate, and nurses' safety performance. Therefore, improving both the occupational and patient safety climate can improve nurses' safety performance, consequently decreasing occupational and patient-related adverse outcomes in healthcare units.

• Journal of Yeungnam Medical Science
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• v.41 no.2
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• pp.134-138
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• 2024

Lung retransplantation (LRT) involves a second or subsequent lung transplant (LT) in a patient whose first transplanted graft has failed. LRT is the only treatment option for irreversible lung allograft failure caused by acute graft failure, chronic lung allograft dysfunction, or postoperative complications of bronchial anastomosis. Prehabilitation (rehabilitation before LT), while patients are on the waiting list, is recognized as an essential component of the therapeutic regimen and should be offered throughout the waiting period from the moment of listing until transplantation. LRT is particularly fraught with challenges, and prehabilitation to reduce frailty is one of the few opportunities to address modifiable risk factors (such as functional and motor impairments) in a patient population in which there is clearly room to improve outcomes. Although rehabilitative outcomes and quality of life in patients receiving or awaiting LT have gained increased interest, there is a paucity of data on rehabilitation in patients undergoing LRT. Frailty is one of the few modifiable risk factors of retransplantation that is potentially preventable. As such, it is imperative that professionals involved in the field of retransplantation conduct research specifically exploring rehabilitative techniques and outcomes of value for patients receiving LRT, because this area remains unexplored.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.50 no.2
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• pp.70-79
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• 2024

Objectives: The surgical guide is a static computer-assisted device used for implant surgery planning and guidance. By taking an impression and referring to the patients' three-dimensional computed tomography scan of the desired implant site, a surgical guide can be created. During surgery, the surgical guide aids in achieving the designed implant placement position and direction. We examined and evaluated the long-term clinical outcomes of implant surgery using surgical guides. Materials and Methods: This study investigated a total of 15 patients with 32 implants that were placed using surgical guides from 2009 to 2011 with a mean follow-up period extended beyond 10 years. Patient demographics and implant survival rates were recorded. We analyzed marginal bone loss (MBL) by assessing the radiographs acquired at installation, three months after installation, and one month, one, two, and five years after prosthesis delivery. Results: The mean patient age was 57.33 years at implant placement. Of the 32 implants, five implants were placed in the anterior region and 27 implants were in the posterior region. Six implants failed and three of them were replaced, resulting in an 81.25% survival rate. The mean follow-up period was 10 years and nine months. Mean MBL compared to post-installation was significantly higher than at three months after installation, and one month, one, two, and five years after prosthesis delivery. Mean MBL at three months after installation, and one month, one year, and two years were significantly higher compared to the previous visit (P<0.05). However, MBL at five years after prosthesis delivery did not differ significantly compared to at two years. Conclusion: In this study, implant rehabilitation assisted by surgical guides exhibited favorable survival rates. With the limitation of the sample amount in this study, further research and more samples are required to evaluate the long-term clinical effectiveness of surgical guides.

• Korean Medical Education Review
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• v.21 no.2
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• pp.80-91
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• 2019

The tripartite mission of 'academic medicine' is education, research, and patient care. Academic medical centers (AMCs) are carrying out the mission and ultimately aiming to improve the health of people and communities. Globally, AMCs are facing a tremendous financial risk stemming from the changes in health insurance reimbursement plans and a shortage of human resources. Innovative AMCs in the United States are trying to transform their physician-centered, and siloed structure into a patient-centered, and integrated structure. They are also building integrated systems with primary healthcare groups to provide continuous patient care from primary to tertiary levels and making strategic networks based on value-based payment and the patient-centered model. These changes have been proven to improve outcomes of patient care and increase fiscal revenues, which are both crucial in supporting education and research. To address the shortage of human resources, programs are being built to develop newly appointed faculty for the future. AMCs have different approaches to bringing changes into their organizations; however, there is a common emphasis on 'a patient-centered approach,' which helps them set more explicit organizational values and make strategic decisions based on their values. Korean AMCs are facing similar challenges to AMCs in the United States in spite of many differences between the countries' healthcare systems. The innovative efforts of AMCs in the United States to address the challenges will be helpful, well-worked examples for Korean AMCs with similar challenges.

• Archives of Craniofacial Surgery
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• v.17 no.1
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• pp.14-19
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• 2016

Background: Most nasal bone fractures are corrected using non-invasive methods. Often, patients are dissatisfied with surgical outcomes following such closed approach. In this study, we compare surgical outcomes following blind closed reduction to that of ultrasound-guided reduction. Methods: A single-institutional prospective study was performed for all nasal fracture patients (n=28) presenting between May 2013 and November 2013. Upon research consent, patients were randomly assigned to either the control group (n=14, blind reduction) or the experimental group (n=14, ultrasound-guided reduction). Surgical outcomes were evaluated using preoperative and 3-month postoperative X-ray images by two independent surgeons. Patient satisfaction was evaluated using a questionnaire survey. Results: The experimental group consisted of 4 patients with Plane I fracture and 10 patients with Plane II fracture. The control group consisted of 3 patients with Plane I fracture and 11 patients with Plane II fracture. The mean surgical outcomes score and the mean patient dissatisfaction score were found not to differ between the experimental and the control group in Plane I fracture (p=0.755, 0.578, respectively). In a subgroup analysis consisting of Plane II fractures only, surgeons graded outcomes for ultrasound-guided reduction higher than that for the control group (p=0.007). Likewise, among the Plane II fracture patients, those who underwent ultrasound-guided reduction were less dissatisfied than those who underwent blind reduction (p=0.043). Conclusion: Our study result suggests that ultrasound-guided closed reduction is superior to blind closed reduction in those patients with Plane II nasal fractures.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.51-59
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• 2012

We describe the framework of a data-fuelled, interdisciplinary team-led learning system. The idea is to build models using patients from one's own institution whose features are similar to an index patient as regards an outcome of interest, in order to predict the utility of diagnostic tests and interventions, as well as inform prognosis. The Laboratory of Computational Physiology at the Massachusetts Institute of Technology developed and maintains MIMIC-II, a public deidentified high- resolution database of patients admitted to Beth Israel Deaconess Medical Center. It hosts teams of clinicians (nurses, doctors, pharmacists) and scientists (database engineers, modelers, epidemiologists) who translate the day-to-day questions during rounds that have no clear answers in the current medical literature into study designs, perform the modeling and the analysis and publish their findings. The studies fall into the following broad categories: identification and interrogation of practice variation, predictive modeling of clinical outcomes within patient subsets and comparative effectiveness research on diagnostic tests and therapeutic interventions. Clinical databases such as MIMIC-II, where recorded health care transactions - clinical decisions linked with patient outcomes - are constantly uploaded, become the centerpiece of a learning system.